International Journal of Vehicle Design (60 papers in press)
Modelling and analysis of spring return electromagnetic valve actuator for SI engine
by Volkan Aygul, Murat Ayaz, Ahmet Necati Ozsezen
Abstract: In internal combustion engines, variable valve timing is one of the most important parameters that affects engine performance, fuel consumption and exhaust emission. In all engine speed values, electromechanical valve actuators (EVA) are needed for variable valve timing. EVAs allow the intake and the exhaust valves to be opened and closed at the right time by the camshaft. The valves can be opened and closed by the magnet circuits, and the opening and closing times can be controlled without depending on the camshaft present in all engines. The most critical part for EVA design is the solenoid in terms of the limited space on the cylinder head, the magnetic force required to open and close the valve, the coil temperature and the valve speed. This study proposes a comprehensive design of piston-type EVA and an analysis of its performance. The simulation results of the analysis with finite element method have been verified with the experimental test results. In addition, the conventional valve profile has been compared with the EVA valve profile.
Keywords: EVA; volumetric efficiency; finite element analysis; variable valve timing; SI engine; mechatronic system design.
Integrated control of active steering and braking systems with tyre forces and cornering stiffness estimation
by Qingwei Liu, Jiannan Luo, Hui Lu, Fan Yu
Abstract: A model-based integrated controller for active steering and active braking systems is proposed to enhance vehicle handling and stability. A hierarchical scheme is adopted, including vehicle layer based on Model Predictive Control (MPC), actuator layer, and observer layer. The MPC controller adopts a predictive model with the lateral force of front axle and yaw moment as inputs, which leaves the nonlinearity and coupling of tyre forces to be solved by the tyre force allocation algorithm in actuator layer, leading to more precise control action. In order to maintain satisfactory control performance with respect to the variation of tyre character, a Dual Extended Kalman Filter (DEKF) is designed in the observer layer to estimate tyre forces and cornering stiffness. The observed results are used to reduce the mismatch of the reference models in vehicle layer and actuator layer. The effectiveness of the proposed controller is demonstrated by simulations in the Carsim environment.
Keywords: integrated control; model predictive control; dual extended Kalman filter; tyre force estimation; tyre cornering stiffness identification.
Methods of automatic calibration for four-wheel alignment based on superimposing angles
by Qi-Xun Zhang, Cheng-Hui Shao, Shuang-Shuang Xu, Yang Song, Zhong-Yuan Zhang
Abstract: The four-wheel aligner is an important piece of testing equipment for calibrating the positional parameters of wheels on vehicles. Reliable and precise four-wheel alignment benefits vehicle running stability, fuel efficiency, safety, and drive comfort. The main alignment parameters include the camber and toe angles of the wheel as well as the caster and inclination angles of the kingpin. We have designed a device suitable for automation that can be used to achieve accurate calibration for four-wheel alignment. It is driven by three direct drive motors to calibrate toe-in angle, camber angle, kingpin inclination angle and kingpin caster angle. Kingpin inclination angle and kingpin caster angle calibrations are based on the angle of formation by one direct drive motor in the horizontal plane; the other motor is mounted on the moving ring of the first motor and is angled in the vertical plane. Accurate synthetic angle mathematical models produce calculations to obtain the kingpin inclination angle and kingpin caster angle. The device has the advantages of a simple structure, a design that is well-suited for automatic control, and a high-precision direct-drive-motor corner control that augments accuracy. It can simulate the true size of the chassis suspension wheel positioning system over a dynamic range of parameters for various models and is applicable to most available four-wheel alignments. The detection precision of the calibration device is one-third to one-fifth the precision of the aligner. The precise design meets the standard technical indicators for calibration.
Keywords: direct-drive manipulator; four-wheel aligner; calibration device; synthetic angle mathematical model.
Steering energy optimisation strategy of steer-by-wire system with dual electric motors
by An Wang, Chunyan Wang, Wanzhong Zhao
Abstract: In order to improve the fault-tolerant ability of a steer-by-wire system, a dual-motor structure is introduced to improve the system reliability as well as the steering safety. However, the redundant motor will change steering energy consumption. Therefore, a dual-motor coupling steering (DMCS) strategy is proposed to minimise steering energy while maintaining steering stability. The proposed control strategy contains two layers, namely an upper stability controller and a lower energy optimisation controller. First of all, stability controller is designed to ensure the operational stability under external interference and model uncertainty. Then, the instantaneous overall efficiency is optimised based on the working point between main and auxiliary motors and the operating principles of energy optimisation controller in various modes are analysed. Last but not least, this paper formulates the optimal mode switch strategy and power split strategy on the premise of satisfying stability during steering process. Simulation results conducted by Matlab/Simulink demonstrate that the DMCS strategy can satisfy the stability demands at different steering conditions and realise the optimal allocation of energy between motors, thereby improving the efficiency of energy use.
Keywords: steer-by-wire system; vehicle stability control; dual electric motors; efficiency optimisation; power split.
Integrated hierarchical control strategy of active suspension and differential assisted steering system for electric-wheel vehicle
by Shuai Wang, Guobiao Shi, Yi Lin
Abstract: In order to solve the performance decrease of riding comfort and handling stability caused by the increase of unsprung mass for the electric-wheel vehicle, an integrated hierarchical control strategy is proposed based on differential assisted steering system and active suspension system. Here, the upper controller is designed to coordinate the overall control strategy and determine the control weight of the two subsystems by the fuzzy control algorithm. Afterwards, for the lower controllers, the linear quadratic optimal algorithm is taken in the differential steering system to determine the additional yaw moment, and the active disturbance rejection control is used in the active suspension system to suppress body vibration and improve riding comfort. The simulation results show that the proposed hierarchical control can effectively improve the riding comfort and handling stability of the electric-wheel vehicle.
Keywords: electric-wheel vehicle; active suspension; differential steering; hierarchical control.
Effects of stacking sequences, inclination angles, and foam thickness of the hood sandwich structures for pedestrian safety using finite element modeling
by Azzam Ahmed, Li Wei
Abstract: The types of material in the automobile hood play an essential role in pedestrian safety, which can be the primary factor in reducing the risk level of head impact during an event of the collision between the front part of the vehicle hood and a human head. The composite materials are used rather than steel and metal, thanks to their higher stiffness, lightweight, and ability to absorb impact energy. In this study, the finite model's design was carried out using ABAQUS/Explicit to predict the actual level protection of structures to pedestrians throughout a collision. The effects of different laminate lay-ups, inclination angle, and foam core thickness of the hood panel on HIC value, displacement, and absorbed energy were investigated and evaluated. The validity of the simulation results is confirmed using the Euro-NCAP assessment process for pedestrian headform impact on a composite sandwich panel. The benefit of this finite element modelling that it could suitably predict the risk level of pedestrian injury.
Keywords: pedestrian head impact; head injury criteria; composite sandwich panel; adult headform; finite element modelling.
Influence of capacity and energy density of lithium-ion battery on thermal reaction during high rate charging
by Xiaogang Wu, Haoqi Guo, Jiuyu Du
Abstract: Long range and fast charging are the future development trends in battery-operated electric vehicles. NCM ternary lithium-ion batteries have been widely used in electric vehicles owing to their high energy density and long cycle life. However, the resultant negative impacts of the increased energy density cannot be ignored, particularly the heat generation problem of the battery under the condition of high rate charging and the performance degradation and safety concerns caused by it. The optimal operating temperature of NCM series batteries ranges from 25
Keywords: high energy density; lithium-ion battery; thermo-physical parameters; capacity and size; high rate charging; temperature rising; heat generation rate.
Investigation into the structure and transmission mechanism of novel multistage face gear transmission based on battery discharge current constant of an electric vehicle
by Xingbin Chen, Qingchun Hu, Zhongyang Xu, Xiaofeng Liang, Jianying Li, Qianli Mai, Chune Zhu
Abstract: The performance and mileage of an electric vehicle (EV) are usually affected by battery capacity and transmission efficiency. We propose a novel power transmission device, which matches the dynamic performance of vehicle under limited conditions, such as motor peak power and battery capacity, to ensure working in the constant battery discharge current and high efficiency. Based on the constant current discharge principle of power battery, aiming at the long driving distance of EV, the optimisation design model of structural parameters is established to yield the best transmission ratio and optimal detailed design parameters. We optimised the Advisor simulation to verify the speed regulated performance and drive efficiency of whole transmission system.
Keywords: Peukert equation; face gear; transmission ratio; multistage; driving distance.
An ease-off based approach to designing a high-order transmission motion for face-milled spiral bevel gears
by Qi Wang, Chi Zhou, Liangjin Gui, Zijie Fan
Abstract: This work proposes an approach for designing a fourth-order transmission motion based on ease-off modification for spiral bevel gears used in trucks. Four control parameters derived from three feature points on a predetermined fourth-order motion graph were proposed to obtain an ease-off modification. Then, the ease-off was used to calculate the machine settings of the pinion. This approach differs from other methods in that the polynomial coefficients of the transmission motion are not directly used to obtain the ease-off. Instead, parameters of the predetermined transmission motion with actual physical meanings are used, avoiding the difficulty of directly assigning values to polynomial coefficients. A semi-analytical loaded tooth contact analysis (LTCA) method is used to obtain the loaded performance. A spiral bevel gear pair in the driving axle is designed and manufactured with a fourth-order transmission motion to show the effectiveness of the approach. The simulated loaded contact pattern shows good agreement with the loaded tooth contact experiment. The results show that the loaded transmission error can be reduced by 29.6%, the maximum contact pressure can be reduced by 10.6%, and the maximum root bending stress can be reduced by 17.4% and 23.8% for the pinion and wheel, respectively. The obtained results indicate good improvements over the original design.
Keywords: spiral bevel gears; fourth-order transmission error; ease-off modification; loaded transmission error; bending stress; loaded contact pattern.
Quantifying parameters of the seat-occupant interface during laboratory simulated low speed rear-impact collisions
by Jackie D. Zehr, Kayla M. Fewster, David C. Kingston, Chad E. Gooyers, Robert J. Parkinson, Jack P. Callaghan
Abstract: The influence of supplemental lumbar support on automobile seat surface pressures was measured during simulated rear impact collisions with human volunteers. Men and women (age = 25.4 +/- 3.4 years; BMI = 25.2(3.9); stature = 1.73 m (0.06)) experienced two low-velocity rear impact collisions. Simulated collisions with and without a lumbar support were conducted in random sequence. Using a pressure-sensing mat that contained 2288 ferroresistive sensors, seatback pressure was recorded at a frequency of 500 Hz. These data were used to compute the total seatback force, area of force concentration, and centre-of-force (CoF). Total seatback force was not significantly different from body mass for either men or women (c. 1.2 times body mass). Average contact area of the occupants back with the seatback (i.e., area of force concentration) was approximately 221.3 cm2 and 100.1 cm2 greater without supplemental lumbar support for men and women, respectively. With respect to the L4 spinal level, the CoF had a greater vertical distance without lumbar support and a greater horizontal distance with lumbar support. In conclusion, the lumbar support used in this study altered the location and distribution of seatback forces applied to the occupants back.
Keywords: lumbar support; rear impact; accidents; low-back injuries; seatback pressure.
Review of latest technological advancement in electro-mechanical continuously variable transmission
by Izhari Izmi Mazali, Nurulakmar Abu Husain, Kamarul Baharin Tawi, Zul Hilmi Che Daud, Mohd Salman Che Kob, Zainab Asus
Abstract: Continuously variable transmission (CVT) is a type of automotive transmission commonly used to achieve minimum fuel consumption. Nevertheless, a conventional CVT applies a hydraulic actuation system, which is powered by the vehicles engine, to vary its ratio and to clamp the metal pushing V-belt accordingly. As a result, a significant portion of the engine power is diverted for the CVTs operation, making the powertrain system significantly less efficient. To address this challenge, many researchers have proposed the idea of electro-mechanical CVT (EM CVT). This paper provides a review of the latest designs of EM CVT, followed by highlights on the relevant research areas that should be pursued so that further advances can be made in EM CVT to bring it closer to commercialisation. These areas are (1) efficiency validation of an EM CVT versus a conventional CVT, (2) durability of the screw-thread system and the thrust bearing, (3) ratio and belt slip controls and (4) packaging of the actuation system.
Keywords: electro-mechanical; continuously variable transmission; ratio control; belt slip control; metal pushing V-belt.
Discrete ratio control strategy of the automotive powertrain with electro-mechanical continuously variable transmission
by Junlong Liu, Dongye Sun, Xiaojun Liu, Yong You, Sheng Liu
Abstract: In the automotive powertrain with electro-mechanical continuous variable transmission (EM-CVT), a small fluctuation of the throttle opening or the velocity will lead to the fluctuation of the EM-CVT speed ratio. However, the speed ratio variation is useless and will increase the energy consumed by the EM-CVT actuator. In this study, a discrete ratio control strategy is proposed to solve this problem. The continuous speed ratio of the EM-CVT is discretised based on discretized engine speed. In order to verify its effectiveness, this ratio control strategy is simulated with the EM-CVT powertrain model using MATLAB/Simulink. The results show that the speed ratio fluctuation is eliminated with the discrete ratio control strategy and the energy consumed by the EM-CVT actuator is reduced, and the results also show that the discrete ratio control strategy has a positive effect on the vehicle comfort performance.
Keywords: vehicle design; automotive powertrain; electro-mechanical continuously variable transmission; discrete speed ratio control strategy; transmission performance.
Robust model referenced control for vehicle rollover prevention with time-varying speed
by Ke Shao, Jinchuan Zheng, Kang Huang, Mingming Qiu, Zhe Sun
Abstract: In this paper, an active steering control strategy is proposed to prevent rollover of a vehicle with a time-varying forward speed. The controller is designed with the aim of reducing the rollover index (RI) from an initial dangerous status to an absolutely safe status by active steering. The controller consists of two parts. The nominal control is firstly designed on the basis of the fundamental equation of constrained motion (FECM) of the vehicle, which will guarantee the nominal vehicle to track the desired states and thus rollover is prevented. To handle system uncertainties, compensatory sliding mode control (SMC) is proposed, by which the actual states are forced to track the desired ones. In the controller, the chattering problem can be alleviated by selecting a suitable performance function. To indicate the merits of the designed controller, simulation is conducted. Simulation results demonstrate that compared with conventional controllers, the proposed controller can prevent the vehicle from rollover with stronger robustness and without system chattering.
Keywords: rollover prevention; active steering; time-varying speed; FECM; SMC; robustness.
Model-based characterisation of vehicle occupants using a depth camera
by Byoung-keon Park, Jian Wan, Ksenia Kozak, Matthew Reed
Abstract: Owing to recent advances in sensing technologies, modern vehicle occupant classification systems enable personalised vehicle experiences and adaptive occupant crash protection. However, most systems are limited to occupant detection and simple classification, and thus, accurate estimation of body characteristics is needed to support more advanced occupant classification. This paper presents a model-based characterisation method for vehicle occupants using a 3D depth camera. This method automatically estimates standard anthropometric data of an occupant, such as stature and weight, along with the body shape by fitting a statistical body shape model to depth image data. The system is even robust to a wide range of clothing and is capable of generating accurate results. A variety of other algorithms were developed to improve the fitting result, including seat geometry detection and head location estimation. The new capability has a range of potential applications for improving occupant safety and providing an optimised interior configuration for the occupant.
Keywords: occupant characterisation; occupant detection; occupant classification; time-of-flight camera; depth camera; statistical body shape model; SBSM; body shape estimation; anthropometry; model fitting.
Slope shift strategy for automatic transmission vehicles based on road slope and vehicle mass identification
by Guang Xia, Ruiqi Yan, Xiwen Tang, Baoqun Sun
Abstract: Road gradient and vehicle mass are estimated using a method with variable forgetting factor, which has strong adaptability and following capability. A control strategy with hierarchical correction is proposed for a vehicle that shifts on a slope. The shifting process is composed of the upper identification decision and lower shift correction executive layers. The upper layer focuses on collecting vehicle parameters, estimating road gradient and vehicle mass, and presenting a modified control decision. The lower layer performs the slope shift schedule from the upper layer. Results of the simulation test are given. Furthermore, the designed strategy can duly downshift the gear uphill and avoid frequent shifting, thereby reducing the wear of the transmission parts and downshifting the gear timely downhill to utilise the torque characteristics of engine braking and reduce the wear of the braking system.
Keywords: double-clutch automatic transmission; forgetfulness factor; slope estimation; mass estimation; shift modification; hierarchical control.
Refined modelling of thin-walled beam, plate and joint for automobile frame
by Jiantao Bai, Wenjie Zuo
Abstract: At the conceptual design stage, the simplified frame is extensively applied in the body-in-white (BIW) structure to rapidly calculate its performances. However, it is difficult to acquire an accurate simplified frame of the BIW structure for the calculation of the bending stiffness, torsional stiffness and frequencies. This paper proposes a simplified modelling method by using the thin-walled beams (TWBs) with complex sections, semi-rigid elements and cross beam structures to create the simplified frame. Compared with the traditional modelling method, the TWBs contain more types of the complex section, the semi-rigid elements can describe various deformations, and the plate structures are further considered. Firstly, the properties of the complex sections are summarised. Especially, the torsional moments of inertia of the multi-cell sections are derived. Secondly, the semi-rigid beam element is reduced to a super element, which is composed of one beam element and three translational and three rotational springs. Among them, the spring stiffness of the semi-rigid element is obtained by solving the detailed finite element model of the TWBs, which can be accurately and rapidly solved by using this method. Thirdly, the cross beam structure is introduced to replace the plate structure by the equivalence of the mass and central deflection for the first time. This method can further improve the accuracy of the simplified frame. Lastly, a numerical example demonstrates that the simplified frame can accelerate the conceptual design of the BIW structure.
Keywords: conceptual design; frame structure; complex section; semi-rigid element; cross beam structure.
Optimal coordinated control of a vehicular platoon by taking into account the individual vehicle dynamics
by Xiujian Yang, Yayong Chen, Jin Gao
Abstract: In most of the previous studies about vehicular platooning control, the individual vehicle in a platoon is simply viewed as a lumped-mass point without considering the dynamics of the vehicle itself, e.g. large slip in braking or accelerating operations. From this point, a novel optimal coordinated platooning control (OCPC) scheme is proposed in this work. In detail, not only the relative motions (vehicle velocity, acceleration) between adjacent vehicles but also the individual vehicle dynamics (wheel rotational dynamics) are taken into account to determine the vehicles following control action (desired acceleration) in a platoon. The OCPC controller is designed as a linear quadratic regulator (LQR), and the coordination of the two control aspects, that is platooning following and individual vehicle dynamics, is realised by regulating the weights in the cost function. For convenience of comparison, an optimal platooning control (OPC) law where the individual vehicle dynamics is not involved is also derived. The string stability and scalability property of the platoon based on the proposed control strategy OCPC are analysed theoretically. Several numerical simulations in time domain are conducted based on a six-vehicle platoon model in which the tyre force is strongly nonlinear to evaluate the proposed control scheme. It is revealed that, in both high and low adhesion conditions, the string stability and scalability can be guaranteed easily and the platooning-following performance can be enhanced as well by the proposed OCPC scheme comparing with the OPC scheme. Especially in low adhesion road condition, the advantage of OCPC over OPC is much more obvious.
Keywords: vehicle dynamics; platooning; string stability; intelligent vehicle.
Artificial road input data synthesis: a full vehicle model case study
by Adebola Ogunoiki, Oluremi Olatunbosun
Abstract: In order to reduce the time and cost of developing a vehicle, it is important that virtual durability testing is carried out. In this research project, the aim is to predict the road input for the virtual durability test simulation of a new vehicle variant by transforming the data from a predecessor model using the vehicle's configuration parameters to generate a new and representative road input. To achieve this, a full vehicle model of a sport utility vehicle (SUV) is developed and validated with test data collected on a proving ground; this model is used to generate data to train and validate a NARX-based artificial neural network tool which is then subsequently used to predict the road input to the new variant of the vehicle. The use of artificial neural networks in this project shows one of the many potentials of artificial intelligence in developing virtual capabilities within the automotive industry.
Keywords: multi-body dynamics; artificial neural network; durability; computer aided engineering; CAE; road load data; RLD; full vehicle model; vehicle variant; QanTiM; SIMPACK; multi-body simulation; MBS.
A novel design of a dry clutch pressure plate for weight reduction without compromising its thermo-mechanical performance
by Tolga Cakmak, Muhsin Kilic
Abstract: The main objective of this study is to conduct experimental research to investigate the effect of ventilation channels that have never been incorporated into the conventional automotive clutch pressure plate. The purpose is to reduce its weight without compromising its thermo-mechanical performance. Both convective and conductive heat transfers of the clutch pressure plate have been enhanced in order to meet thermo-mechanical performance requirements, by ventilation channels and by chemical composition adjustment, respectively. The novel design of ventilated
Keywords: dry clutch; heat transfer enhancement; weight reduction.
Special Issue on: Multi-Objective Design and Structural Optimisation of Vehicle Components with Nature-Inspired Optimisation Algorithms
Determination of dynamic axle load using suspension deflection method for the load distribution optimisation of multi-axle vehicles
by Mustafa Umut Karaoğlan, Nusret Sefa Kuralay
Abstract: Identification of dynamic axle loads in multi-axle vehicles requires complex calculation methods because of the hyperstatic solving necessity. Existing methods for identification of axle loads are mostly based on response simulation by using a beam element to overcome the hyperstatic problem using numerical solutions. In this study, a suspension deflection method is proposed to determine the dynamic axle loads to optimisation of load distribution of a multi-axle vehicle having more than two axles. Load distribution optimisation for each axle is required for the definitions of maximum and minimum weights of the vehicle dynamically to provide better vehicle handling dynamics and axle strength. The determination of the dynamic axle loads is performed for a driving conditions with a climbing angle and a longitudinal acceleration to optimise the loads at the axles of the vehicle using a suspension deflection method. General equations and calculation methodology are presented for a multi-axle vehicle. Then, a numerical example is implemented using the suspension deflection method for a four-axle vehicle as a case study. The effect of the wheelbase, acceleration, climbing and characteristics of the suspension spring on load distribution are investigated for the optimisation of the loads on each axle of the vehicle. Finally, it is shown that the suspension deflection method is more simple and useful than other approaches to define the dynamic axle loads for an optimisation study of vehicles with multiple axles.
Keywords: axle load optimisation; suspension deflection method; multi-axle vehicles; load distribution.
Grey wolf optimiser in the design of leaf springs of railway vehicles
by Milan Bizic, Goran Markovic, Radovan Bulatovic, Dragan Petrovic, Milan Dedic
Abstract: The paper deals with the usage of the Grey Wolf Optimiser (GWO) in the optimal design of leaf springs for railway vehicles. The main goal is minimisation of the mass of leaf springs, with retention required characteristics of suspension system. Based on the exposed analytical model of leaf springs and requirements for suspension system, an optimisation model is developed. The developed model and GWO are applied in the optimal design of leaf spring of 4-axle freight wagon for an axle load of 200 kN. The results have shown that the proposed model and GWO provide a significant reduction of the mass of leaf springs of about 46.7%, in relation to the conventional design method. In addition, a numerical model of leaf springs is developed and the design obtained by GWO is verified by FEM calculation. the proposed approach enables significant material savings and reduction of production costs, as well as the reduction of design time of leaf springs of railway vehicles.
Keywords: grey wolf optimiser; optimal design; leaf springs; railway vehicles.
Robust topology optimisation design of the guiding arm bracket for vehicle suspension
by Xiaokai Chen, Dong Fu, Junbin Fan, Mengqiang Li
Abstract: Based on the theory of stochastic collocation method, the uncertain factors of the guiding arm bracket were simulated, and the optimal design was completed with the aim of minimising the structural flexibility. Firstly, the mathematical description of the uncertain factors was discussed. The sparse grid technique was used to filter the obtained integral nodes to improve the computational efficiency. Then, the optimal value and robustness of the objective function were described by using the mean and variance respectively. Combining with the stochastic collocation method, the mathematical model of the robustness optimisation was established. Finally, the feasibility of the robust topology optimisation design method was verified by the suspension guiding arm bracket. The results show that the robust and reliable conceptual model can be obtained by using the sparse grid technique, and choosing the appropriate precision and variables can realise a good compromise between simulation economy and simulation precision.
Keywords: guiding arm bracket; lightweight design; topology optimisation; robustness design; size optimisation.
Optimal design of planetary gear train for automotive transmissions using advanced meta-heuristics
by Hammoudi Abderazek, Sadiq Mohammed Sait, Ali R. Yildiz
Abstract: In this paper, firefly algorithm (FA), interior search algorithm (ISA), Jaya (JAYA) algorithm, multi-verse optimization (MVO), hybrid firefly and particle swarm optimization (HFPSO), neural network algorithm (NNA), roulette wheel selection-elitist differential evolution (ReDE), hybrid grey wolf and cuckoo search (GWO_CS), and butterfly optimisation algorithm (BOA) have been employed to find the optimal design of an automatic planetary gear train. The designed system is used to automatically transmit the power and motion in automobiles. Nine mixed decision parameters are considered in the optimisation procedure. The geometric conditions, such as the undercutting phenomenon, the maximum overall diameter of the transmission, as well as the spacing of multiple planets, are taken into account to ensure an optimum design of the system. All the above algorithms are tested quantitatively and qualitatively for solution quality, robustness, and time complexity. The optimisation results illustrate that the used approaches can effectively solve the planetary gearbox problem. Besides, the comparative study indicates that ReDE outperforms the other algorithms in terms of the statistical results, and FA has the best convergence behaviour. Meanwhile, MVO and BOA performed better than the other used algorithms when the computation time was considered.
Keywords: planetary gearbox; automotive transmissions; discrete optimisation; optimal design; meta-heuristics.
Comparison of recent algorithms for many-objective optimisation of an automotive floor-frame
by Natee Panagant, Nantiwat Pholdee, Kittinan Wansasueb, Sujin Bureerat, Ali R. Yildiz, Sadiq M. Sait
Abstract: In this paper, an approach called real-code population-based incremental learning
hybridised with adaptive differential evolution (RPBILADE) is proposed for solving many-objective automotive floor-frame optimisation problems. Adaptive strategies are developed and integrated into the algorithm. The purpose of these strategies is to select suitable control parameters for each stage of an optimisation run, in order to improve the search performance and consistency of the algorithm. The automotive floor-frame structures are considered as frame structures that can be analysed with finite element analysis. The design variables of the problems include topology, shape, and size. Ten optimisation runs using various optimisers are carried out on two many-objective automotive floor-frame optimisation problems. Twelve additional benchmark tests against all competitors are also performed to demonstrate the search performance of the proposed algorithm. RPBILADE provided better results than other recent optimisers for both the automotive floor-frame optimisation and benchmark problems.
Keywords: automotive floor-frame design; many-objective optimisation; population-based incremental learning; differential evolution; adaptive algorithm.
Automated design of aircraft fuselage stiffeners using multiobjective evolutionary optimisation
by Kittinan Wansasueb, Ruangrit Sarangkum, Natee Panagant, Nantiwat Pholdee, Sujin Bureerat, Ali R. Yildiz, Sadiq M. Sait
Abstract: This paper proposes an optimisation process for synthesising aircraft fuselage stiffeners by using evolutionary optimisation. A new design problem is assigned to find a layout of fuselage stiffeners (rings and stringers) such that optimising structural mass, compliance, and the first-mode natural frequency are subject to structural constraints. The stiffeners are modelled as beam elements. Three multiobjective meta-heuristics are employed to solve the design problem. The results obtained are compared. It is found that the proposed layout synthesis problem for aircraft fuselage stiffeners leads to a set of efficient structural solutions, which can be used for the decision-making stage. It is an automated design strategy with high potential for further investigation.
Keywords: aircraft fuselage; multiobjective optimisation; rings and stringers; fuselage stiffeners; meta-heuristics.
Optimisation of pedestrian detection system using FPGA-CPU hybrid implementation for vehicle industry
by Ahmet Remzi Ozcan, Vedat Tavsanoglu
Abstract: Better image processing and developing technologies are rapidly expanding the application areas of image processing systems. In recent years, pedestrian detection systems have become one of the major safety technologies used in the automotive industry. This paper presents an optimised real-time pedestrian detection system using an FPGA-CPU based hybrid design. The Histograms of Oriented Gradients (HOG) algorithm, which is extensively used for feature extraction in pedestrian detection applications, was implemented on a low-end FPGA. In the study, the original HOG descriptors are designed in low complexity without sacrificing performance. The obtained features were classified on a low-power single board computer with support vector machine (SVM). Tests with the INRIA pedestrian database show that the proposed model has high potential for use as a real-time low-cost pedestrian detection system in practice.
Keywords: optimisation; vehicle design; histogram of oriented gradients; computer vision; pedestrian detection; FPGA.
Multi-surrogate-assisted metaheuristics for crashworthiness optimisation
by Chomar Aye, Nantiwat Pholdee, Ali R. Yildiz, Sujin Bureerat, Sadiq M. Sait
Abstract: This work proposes a multi-surrogate-assisted optimisation and performance investigation of several newly developed metaheuristics (MHs) for the optimisation of vehicle crashworthiness. The optimisation problem for car crashworthiness is posed to find the shape and size of a crash box while the objective function is to maximise the total energy absorption subject to a mass constraint. Two main numerical experiments are conducted. Firstly, the performance of different surrogate models along with the proposed multi-surrogate model is investigated. Secondly, several MHs are applied to tackle the proposed crashworthiness optimisation problem by employing the best obtained surrogate model. The results reveal that the proposed multi-surrogate model is the best performer. Among the several MHs used in this study, sine cosine algorithm is the best algorithm for the proposed multi-surrogate model. Based on this study, the application of the proposed multi-surrogate model is better than using one particular traditional surrogate model, especially for constrained optimisation.
Keywords: surrogate-assisted optimisation; crash box design; evolutionary algorithm; constrained optimisation; meta-heuristics.
A new hybrid salp swarm algorithm and radial basis function-based approach for robust design of vehicle control arm
by Betül Sultan Yildiz
Abstract: Considering the light-weight design expectations and government requirements in the automotive industry, both structural optimisation approaches and swarm intelligence methods have been receiving gigantic attention for their high accuracy and robustness. This paper presents the topology and shape optimisation of a vehicle control arm considering stress constraint conditions. The primary purpose of the design is to minimise weight while meeting the stress constraint conditions. There is a growing interest in designing light-weight and low-cost vehicles. In this research, a new hybrid salp swarm-Nelder-Mead (HSSA-NM) algorithm is developed and used to optimise a vehicle control arm. Both Latin hypercube sampling methodology and radial basis function surrogate modelling approach are used for obtaining equations of constraints and objectives used in the shape optimisation. Initially, the performance of the HSSA-NM is tested using a coil spring problem. Finally, the HSSA-NM is used for the optimum design of a vehicle control arm. As a result, a design problem is solved using the HSSA-NM. The optimal design meets all of the problem constraints and reduces the weight by about 2056 grams compared with that of the initial model. Thus, the proposed design method is an efficient method for shape optimisation design.
Keywords: multiverse algorithm; vehicle design; control arm; shape optimisation.
A comparative study on the optimal non-linear seat and suspension design for an electric vehicle using different population-based optimisation algorithms
by Ahmet Yildiz
Abstract: This paper is concerned with the comparative study on the optimal nonlinear seat and suspension design for an in-wheel motor-driven electric car using half vehicle model by integrating different population-based optimisation techniques. The vehicle and the human body are modeled as an eleven-degree of freedom mechanical system. The equations of motion obtained from this model are employed to determine the optimal values leading to better ride comfort by means of different optimisation methods, such as Particle Swarm Optimization (PSO), Differential Evolution (DE), and Genetic Algorithm (GA). Since the nonlinear approach reflects more realistic vibration behaviour than the linear one, the seat and suspension springs are assumed to have cubic progressive characteristics in the mathematical model. An objective function is proposed according to the feasible ideal solution of the root-mean-square (RMS) values of the seat, vehicle, and head accelerations and the suspension deflections. The nine design variables to be optimised are the linear and nonlinear parameters of the seat, rear and front suspensions springs and the dampers. It is observed that overall vibration amplitudes are significantly reduced as the optimisation results of the suspension are used. Furthermore, the results demonstrate that while all three techniques can provide a better reduction in vibration amplitudes than each other in different cases, the PSO algorithm always gives optimal solutions faster than the other techniques meaning that it spends less CPU time.
Keywords: half vehicle model; nonlinear design; in-wheel motor; electric vehicle; seat; suspension; optimisation; PSO; DE; GA.
HKn-RVEA: a novel many-objective evolutionary algorithm for car side impact bar crashworthiness problem
by Gaurav Dhiman, Amandeep Kaur
Abstract: In this paper, a novel hybrid many-objective evolutionary algorithm, named as Hypervolume Indicator based on Knee Point Driven and Reference Vector Guided Evolutionary Algorithm (HKn-RVEA) is proposed. HKn-RVEA is based on the hypervolume indicator, knee points, and reference vector adaptation strategies. The knee points are used to improve the search ability. The reference vectors are used to decompose the optimisation problem into a number of sub-problems. In the proposed algorithm, an adaptation strategy is used to adjust the distribution of the knee points and reference vectors. The proposed algorithm is compared with five well-known evolutionary algorithms over standard benchmark test functions. The results show the better performance of HKn-RVEA than the competitor algorithms in terms of inverted generational distance and hypervolume performance measures. The computational complexity of the proposed algorithm is also analysed. The statistical test is performed to show the significance of the proposed algorithm. HKn-RVEA is also applied to a real-life car side crashworthiness problem to demonstrate its efficiency. The experimental results show that the proposed algorithm is able to solve many-objective real-life problems.
Keywords: many-objective optimisation; hypervolume estimation algorithm; reference vector guided evolutionary algorithm; knee points; convergence; diversity.
Slime mould algorithm and kriging surrogate model-based approach for enhanced crashworthiness of electric vehicles
by Betül Sultan Yildiz
Abstract: Especially since the last decade, electric vehicles have been used frequently in most of the developed and developing countries. With the establishment and expansion of charging station infrastructures, fossil fuel vehicles will inevitably be replaced by electric vehicles in the next ten years. For this reason, electric vehicle components need to be developed very quickly. This paper concentrates on designing a new thin-walled energy absorber to be used in the design of electric vehicles. The material of the thin-walled energy absorber developed in this paper is cold-rolled advanced high-strength steel, which is Docol 1300. In this paper, a comparative study of the recent optimisation algorithms such as slime mould algorithm (SMA), salp swarm algorithm(SSA), and water cycle algorithm (WCA) are presented for optimum design of an automobile energy absorber. This research presents the first application of the slime mould algorithm to the optimum design of automobile components in the literature. The design problem aims to find optimum geometry while minimising mass and meeting energy absorption constraints. Function evaluations are carried out using finite element analysis and estimated by using the kriging surrogate model. The results show that both the SMA and Docol 1300 advanced high-strength material provide exceptional features for enhancing crashworthiness in electric vehicle design, simultaneously.
Keywords: slime mould algorithm; water cycle algorithm; salp swarm algorithm; electric vehicles; energy absorber; optimum design; Docol 1300; advanced high-strength steel.
Mechanical engineering design optimisation using novel adaptive differential evolution algorithm
by Hammoudi Abderazek, Ali Riza Yildiz, Sadiq Mohammed Sait
Abstract: Solving practical mechanical problems is considered as a real challenge for evaluating the efficiency of each new developed algorithm. The present paper introduces a new adaptive mixed differential evolution (NAMDE) for mechanical design optimisation problems. The developed algorithm uses the self-adaptive mechanism in order to update the values of mutation and crossover factors. The feasibility rules are used in the selection phase to improve the search capability of NAMDE. Moreover, the elitism is performed to keep the best individual found in each generation. To handle the constraints the normalisation method is used to treat each constraint design equally. The performance of NAMDE is evaluated by solving five well-known constrained engineering benchmarks, seven mechanical design problems and the practical case of optimal weight design of spur gear. Further, the comparison results between the NAMDE and other recently published methods, for the first 12 problems, illustrate clearly that the proposed approach is an important alternative to solve real-world optimisation problems. Besides, new optimal solutions for some engineering problems are obtained in this article. For the case study, the final design provides a reduction in gearing masses by 7.5% compared with the previous works.
Keywords: differential evolution algorithm; adaptive parameter control; engineering design optimisation; constrained optimisation problems.
Experimental and numerical fatigue-based design optimisation of clutch diaphragm spring in the automotive industry
by Alper Karaduman, Ali Yildiz
Abstract: In the present study, the fatigue behaviour of a clutch diaphragm spring is investigated experimentally and numerically. Differential evolution optimisation algorithm and response surface methodology are used to define optimal variables of the diaphragm springs under constraints both minimum stress and required clamp load. The required clamp load is checked by the chi-square theorem versus to target clamp load curve. Ten design variables are considered for creating a design of experiment with two steps, including finger shape optimisation with eight variables, load, and stress optimisation with two variables as the aim of maximum fatigue definition. One hundred seventy-five different designs are analysed numerically. As a result of the optimisation study, the optimum design is provided an endless lifetime subject to the required load, minimum stress, and minimum weight. The optimum design is manufactured and tested experimentally.
Keywords: optimisation; clutch; diaphragm spring; fatigue.
Integrated optimisation of two-speed powertrain parameters and shifting strategy for energy in electric vehicle
by Daoguang Zhu, Congbo Li, Lingling Li, Ying Tang
Abstract: In order to improve the economic performance and extend the range of electric vehicles (EV), an integrated optimisation method for the design and optimisation for powertrain parameters and shifting strategy are proposed. Firstly, the powertrain parameters are matched to ensure the dynamic performance of electric vehicles and the shifting strategy with comprehensive performance is designed based on the analysis of dynamic and economy performances. Secondly, a multi-objective integration model of powertrain parameter and shifting strategy optimisation is proposed to take the minimum energy consumption as the optimisation objective without sacrificing dynamic performance, which is solved by a multi-objective particle swarm optimisation algorithm. Finally, to verify the energy-saving performance of the proposed multi-objective integration problem, case studies have been conducted and a whole vehicle simulation model is proposed based on Matlab/Simulink platform. The simulation results show that the proposed method can effectively reduce the energy consumption and extend the range of electric vehicles under different driving cycle.
Keywords: electric vehicle; powertrain parameter; shifting strategy; multi-objective integrated optimisation; particle swarm optimisation algorithm.
Marine predators algorithm and multi-verse optimization algorithm for optimal battery case design of electric vehicles
by Betül Sultan Yildiz
Abstract: This article focuses on the optimum design of a battery case of an electric racing car. Two recently developed metaheuristics, which are marine predators algorithm (MPA) and the multi-verse optimisation algorithm (MVO), are used to create an optimal design where the mass is considered as an objective function, and the geometric dimensions of the component are considered to be the design variables. The kriging surrogate modelling is used to obtain the proxy model to increase the efficiency of the optimisation. The results show the robustness of the MPA in the optimum design of the electric car components. The MPA can be used in other product development processes.
Keywords: marine predators algorithm; electric vehicles; battery case; shape design optimisation; multi-verse optimisation algorithm.
Special Issue on: Recent Advances in Motion Control for Unmanned Marine Vehicles
Research on motion control of an autonomic launch and recovery device for unmanned surface vehicles
by Xiaomao Li, Xingang Jiang, Yang Yang, Yan Peng, Songyi Zhong, Huayan Pu, Shaorong Xie, Jun Luo
Abstract: In this study, a floating bracket device with visual inspection technology is developed for the autonomous launch and recovery of unmanned surface vehicles (USVs). To improve the success rate of docking between USVs and brackets in the recovery process, a reasonable controller is proposed to realise the position/posture regulation of the bracket. The state space equation is used to establish a system model, and the specific parameters are identified by using collected motion data. A sectional-type control framework is designed by model predictive control (MPC), which can satisfy the control requirements in different motion stages. The simulation results verify the accuracy of the identification model and the rationality of the MPC controller. The docking experiments demonstrated that the floating bracket with the proposed control system can be applied to launch and recovery missions of USVs.
Keywords: launch and recovery; unmanned surface vehicles; motion control; model predictive control; parameter identification.
Three-dimensional trajectory tracking control of underactuated autonomous underwater vehicles
by Zhenzhong Chu, Xuan Zhang, Daqi Zhu
Abstract: This study proposes a three-dimensional (3-D) trajectory-tracking control scheme for an underactuated autonomous underwater vehicle (AUV). Given the 3-D reference trajectory, the reference velocities, angles, angular velocities, forces, and torques were planned first. These reference variables were used to obtain the error dynamics. The backstepping technique was used to design the trajectory-tracking controller for tracking the AUVs reference trajectory. According to the Lyapunov stability theory, the trajectory-tracking system was stable and bounded, and the tracking errors converged close to a small neighbourhood of zero. Finally, the effectiveness of the developed control method was demonstrated using simulations.
Keywords: autonomous underwater vehicle; three-dimensional control scheme; trajectory tracking; backstepping.
Network-based sampled-data control for unmanned marine vehicles with dynamic positioning system
by Minjie Zheng, Shenhua Yang, Lina Li
Abstract: This study investigates the network-based control problem for an unmanned marine vehicle (UMV) based on sampled data. Firstly, the network-based model for the UMV with dynamic positioning system (DPS) is established. Then sufficient conditions are provided to make the system asymptotically stable and satisfy H? performance. And the sampled-data controller is designed by analysing the stability conditions. Simulation result is shown that the sampled-data controller is effective to guarantee that the states of the UMV are stable under the external disturbance.
Keywords: unmanned marine vehicle; dynamic positioning system; network-based control; sampled-data control.
Sliding mode control design for active suspension systems using quantum particle swarm optimization
by Shouwei Wei, Xiaoyu Su
Abstract: In this paper, the problem of sliding mode control design for nonlinear 1/4 active suspension under road excitation most in line with the real situation is investigated. By using the theory of differential geometry, the suspension model is linearised. The sliding mode controller based on exponential approach law is adopted. The Quantum Particle Swarm Optimization (QPSO) algorithm is used to optimise the switching function C. The ratio of the RMS value of the performance index is used to construct the fitness value to improve the dynamic performance of the system. Three common white noise pavement design methods are compared to select the road excitation of this study. The simulation results show that suspension with sliding mode controller based on QPSO outperforms the ordinary sliding mode control suspension and fuzzy control suspension. The results also prove the importance of sliding surface parameter selection and the superiority and effectiveness of this control method.
Keywords: sliding mode control; active suspension; quantum particle swarm optimization;road excitation.
Trajectory tracking of underactuated unmanned surface vehicle with uncertain external disturbances and model parameters
by Jianjian Liu, Meijiao Zhao, Yan Peng, Dan Zhang, Shaorong Xie
Abstract: This paper investigates trajectory tracking control problem for an underactuated unmanned surface vehicle under external disturbance and model parameters uncertainty. Within the framework of backstepping control, a trajectory tracking control method based on constant bearing guidance is proposed, which can avoid the singularity that often appears in circular motion of the vehicles by redefining the differential of virtual heading angle. Moreover, disturbance observers are designed to estimate the equivalent disturbance, so that the vehicle can track the desired trajectory stably in the unknown ocean environment. Finally, owing to the limitation of the propellers mechanical performance, dynamic saturation of surge force and yaw moment is designed according to the upper and lower limits of two propellers' thrust to ensure the stable operation of the control system. Based on Lyapunov stability theory, the stability of the system is proved. And the numerical simulation results show the effectiveness of the presented control method.
Keywords: underactuated unmanned surface vehicle; trajectory tracking; backstepping; disturbance observer; dynamic saturation.
State observer-based adaptive fuzzy backstepping point stabilisation control of underactuated unmanned surface vehicles with input constraints
by Weixiang Zhou, Pingfang Zhou, Zheng Chen, Dengping Duan
Abstract: In this study, the point stabilisation control of an underactuated unmanned surface vehicle (USV) is addressed considering input constraints, missing velocity measurement and external disturbance. Different from other methods, in this proposed control framework, the point stabilisation is transformed into a straight line path-following problem. Then a state observer-based adaptive fuzzy backstepping controller is designed. The missing velocity variables are estimated by an extended state observer (ESO). An adaptive fuzzy algorithm is used to approximate the unknown nonlinear items in the dynamics model of the vehicle, and auxiliary items are introduced to deal with the actuator saturations. The system stability is proved by using Lyapunov theory, and the effectiveness of the proposed approach is demonstrated by the simulation results.
Keywords: Point stabilization; Underactuated unmanned surface vehicle; State observer; Adaptive fuzzy method; Backstepping control; Input constraints.
Formation control for underactuated unmanned surface vehicles based on consistency theory and leader-follower mode
by Limei Jiang, Rubo Zhang, Naifeng Wen, Guanqun Liu, Junwei Wu, Xingru Qu, Xiao Liang
Abstract: The formation involving multiple unmanned surface vehicles (USVs) is a new hotspot in research on USVs. Considering the formation control problem of underactuated USVs, a distributed formation control algorithm is proposed based on consistency theory and leaderfollower mode. The motion processes of the reference USV with respect to each USV are obtained with a consistency algorithm. By adjusting the control input, each USV converges to the reference vehicle. Thus, the expected formation of all USVs can be guaranteed if the trajectories of these two types of USV coincide. The entire formation uses distributed control, which has certain tolerance to special situations, such as communication delay and communication interruption. The effectiveness of the control strategy is verified through simulations.
Keywords: unmanned surface vehicle; formation control; stability; backstepping.
Investigating capacity degradation of LiFePO4 batteries for electric vehicles under different overcharge conditions
by Xiaogang Wu, Xu Han, Jiuyu Du
Abstract: When the state of charge (SOC) estimation by a battery management system (BMS) is inaccurate or the battery balance fails, the power battery in an electric vehicle may be overcharged, which results in a decline in the capacity and performance of the battery. In this paper, commercial large-format LiFePO4 batteries were used as overcharge targets and different overcharge paths and overcharge cut-off states of charge (SOCOC) were adopted to study the influence of different overcharge conditions on battery performance decay. The experimental results showed that different charge rates in the 0~80% SOC phase also had a certain degree of influence on the performance decay of the overcharged battery, but the SOCOC is the main reason for decline in battery performance. At the same time, battery performance after overcharge was not stable and a series of phenomena occurred when the battery was charged and discharged at a standard rate (1/3C). These phenomena included capacity recovery, synchronous recovery of the time of the constant voltage-charging segment, and charging capacity ratio of the constant voltage-charging segment. The battery discharge capacity overcharged to 110% and recovered from 59.7% to 68.4%. One battery which was overcharged to 105% recovered from 58.2% to 96.5% and the other battery recovered from 86% to 97.5%.
Keywords: electric vehicle; battery; overcharge; capacity degradation; capacity recovery.
High-gain-observer based adaptive output-feedback formation control for underactuated unmanned surface vessels with input saturation and uncertainties
by Meijiao Zhao, Huayan Pu, Yueying Wang, Jun Luo, Shaorong Xie, Yan Peng
Abstract: An adaptive output feedback formation control strategy based on a high gain observer has been developed to solve the problem of the control of underactuated surface vessels formation with uncertain dynamics, ocean environment disturbance and input saturation. In this strategy, a high gain observer that only depends on position information is used to estimate the unmeasurable velocity, and in order to solve the 'complex explosion' problem in the conventional backstepping control algorithm, a first-order low-pass filter is adopted to obtain the derivative of the virtual control signal. In addition, adaptive neural networks (NNs) and minimum learning parameters (MLP) algorithms are used to approximate environmental disturbances and uncertain dynamics, while reducing online update parameters. Stability analysis proved that all signals in closed-loop are uniformly ultimately bounded and the formation tracking errors are arbitrarily small. Simulation results demonstrate the effectiveness of the controller.
Keywords: output feedback; adaptive; backstepping; neural networks; formation control; high gain observer; underactuated surface vessels; input saturation; uncertainty.
Motion reliability evaluation of a six-axes robot based on non-probability interval theory
by Haimiao Wu, Guohua Cui, Peng Chen, Hongjuan Hou
Abstract: The error of position and posture of a robot end operator can affect the posture positioning accuracy. Therefore, an analysis study of motion reliability is important for ensuring the motion safety and normal operation of robots. Considering the effects of the link size deviations and joint clearance on the robot end operator, the error model of position and posture were analysed based on the non-probability interval theory. Then the time-varying motion reliability evaluation model of the robot was established using non-probability interval theory, and the motion reliability variation of the robot during trajectory points were obtained. The optimum design of the robot model was established by taking the deviations of the link size deviations and joint clearance as the optimisation variables, and reasonable ranges of link parameters were determined. The proposed analysis method lays a foundation for further upgrading the robot end operators position and posture accuracy.
Keywords: robot; interval uncertainty theory; motion reliability; optimisation design.
Special Issue on: Fault Diagnosis and Reliable Control for Vehicle Powertrain Systems
Plug-in HEV energy management strategy based on SOC trajectory
by Jing Lian, Xinran Wang, Linhui Li, Yafu Zhou, Shuzhou Yu, Xiujie Liu
Abstract: This paper proposes a predictive control algorithm constrained by the State Of Charge (SOC) trajectory for the Plug-in Hybrid Electric Vehicle (PHEV) hybrid system. Firstly, the hybrid system energy consumption model is linearised in piecewise and the mixed logic dynamics (MLD) model of PHEV with the minimum equivalent fuel consumption as the optimal cost function is established. Secondly, Long Short-Term Memory (LSTM) network is used to forecast the vehicle speed through the historical vehicle speed data. Finally, the SOC trajectory curve is obtained as the constraint condition according to the change of vehicle speed. The optimal motor torque control sequence in the vehicle driving speed prediction horizon is calculated by the model predictive control strategy. The simulation results on different standard operating conditions show that the energy consumption of the PHEV is successfully reduced under the constraints of SOC trajectory.
Keywords: PHEV; LSTM; MPC; SOC trajectory.
An energy-efficient torque distribution strategy for in-wheel-motored electric vehicles based on model predictive control
by Bingtao Ren, Weiwen Deng, Hong Chen
Abstract: In order to improve the energy efficiency (EE) for in-wheel-motored electric vehicles (IWM EVs), an optimal torque distribution algorithm is investigated based on model predictive control (MPC). Firstly, an energy efficiency optimisation structure is developed by considering the energy efficiency characteristics of the motor and the energy loss of tyre slip. To achieve the driving requirements, an upper layer controller is designed to determine a desired motor torque, which takes into account the maximum capacity of the motor drive and regenerative braking. Then, a torque distribution algorithm in the lower layer applies MPC strategy to deal with this energy efficiency optimisation problem with system dynamic and torque saturation constraints. Then to obtain the optimal motor torques fast, an efficient solution approach is given by exploiting the particular structure of the problem and combining constraint conversion and numerical methods. Finally, simulation results in different driving cycles indicate that overall energy efficiency and computational efficiency of the vehicle can be improved. Also, the real-time control performance is guaranteed in the hardware-in-the-loop simulation.
Keywords: optimal control; electric vehicle; model predictive control; energy distribution.
Research on multi-mode regenerative braking energy recovery of electric vehicle with double rotor hub motor
by Liwei Zhang, Ren He
Abstract: In this study, a new type of double rotor hub motor is proposed. Then, its structure, the working principle and the regenerative braking energy recovery modes are described. In detail, three kinds of regenerative braking energy recovery mode, i.e. double motor regenerative braking mode, single inner motor regenerative braking mode and single outer motor regenerative braking mode, are introduced. The mathematical models of the single wheel dynamics model and the double rotor hub motor model are established. The three kinds of braking energy recovery mode are compared and the simulation results show that by using the sliding mode control strategy, on the condition that the maximum braking energy recovery of the motor is satisfied, the hydraulic braking torque can make corresponding response according to the change of the regenerative braking torque of the motor. At the same time, antilock braking of the wheel is achieved.
Keywords: electric vehicle; double rotor hub motor; regenerative braking mode.
Active steering PMSM speed control with wavelet neural network
by Mingzhu Xu, Zhaohan Huo, Shaohua Li, Li Jiang
Abstract: In view of the high requirements of active steering system on the noise, vibration and weight of the motor, this paper chooses the permanent magnet synchronous motor as the active power steering motor. A speed control strategy of this motor based on wavelet neural network PID is proposed. According to the change of system operation parameters, a three-layer feedforward artificial neural network is used to update the PID parameters online training based on gradient descent correction error method. Wavelet neural network and incremental PID are used to construct the speed loop controller. A control system based on DSP28335 is designed for experimental verification. The results show that the proposed control strategy has better static and dynamic performance, which can provide a new choice for small motor control of vehicles.
Keywords: active steering motor; permanent magnet synchronous motor; wavelet neural network; incremental PID.
Path tracking controller design for autonomous vehicle based on robust tube MPC
by Chuanyang Sun, Han Dong, Xin Zhang
Abstract: A robust tube MPC controller based on tube-division with a linear time-varying (LTV) model is proposed for autonomous vehicle path tracking. To reduce the conservativeness, a novel offline method is designed to calculate the tubes by dividing the original N-steps invariant sets into sequences of tighter candidate tubes. The propagation limits of the vehicle time-varying parameters within a prediction horizon are used in the division to ensure each candidate tube contains any state trajectory starting at its origin. A corresponding tube will be selected instead of being calculated online at each sampling instant in terms of vehicle states, which makes a more efficient online computation. The results of the simulation show the improved performance of the proposed robust tube MPC controller.
Keywords: path tracking; robust tube MPC; autonomous vehicle; time-varying system; invariant sets.
Heavy-duty vehicle longitudinal automation with hydraulic retarder via H infinity control and off-policy reinforcement learning
by Chaoxian Wu, Xuexun Guo, Bo Yang, Xiaofei Pei, Zhenfu Chen
Abstract: The longitudinal automation of a heavy-duty vehicle (HDV) is able to improve the safety, efficiency, and productivity of HDVs. However, the excessive use of the friction brake in a long downhill road to track the desired vehicle velocity in the deceleration process can overheat the brake pads, which can compromise the braking performance of the HDV and lead to dangerous situations. The hydraulic retarder is often employed to apply additional braking force to handle these situations in an HDV. However, according to the results of our experiments, the disturbance from the retarder oil temperature has a great impact on the retarder torque and strong nonlinearity, hence it is difficult to build its mathematical model and can severely compromise the retarder torque control accuracy and the speed tracking performance. In this paper, we propose a novel hierarchical HDV longitudinal control strategy with a hydraulic retarder to achieve the HDV downhill longitudinal automation in the deceleration process. The upper level controller generates the optimal desired retarder torque through the H infinity control and the off-policy reinforcement learning (RL), in which the H infinity control is able to attenuate those disturbances and the off-policy RL can solve the H infinity control with completely unknown system dynamics. Then, according to the optimal desired retarder torque, the lower level controller can calculate the desired control pressure for the retarder to control the HDV. The effectiveness of this HDV longitudinal control strategy is verified by simulations based on an experimentally verified retarder model. Compared to the sliding-mode-control based controller, the simulation result shows the proposed control strategy has better capability to attenuate the disturbances and guarantee the longitudinal speed tracking performance.
Keywords: heavy-duty vehicle; longitudinal control; H infinity control; reinforcement learning; hydraulic retarder.
Multi-step torque distribution for an over-actuated electric vehicle
by Houhua Jing, Zhiyuan Liu
Abstract: The over-actuated electric vehicle can flexibly adjust the torque of four wheels, to improve operational efficiency and vehicle motion performance. A multi-step torque distribution strategy is proposed, which can comprehensively consider the energy optimisation, vehicle stability and actuator dynamics, and realise the comprehensive control of longitudinal and lateral motion. It is composed of a static control allocation for energy optimisation, and a dynamic control allocation for manoeuvrability and stability enhancement based on model predictive control. It does not rely on complex online optimisation and is adaptive to highlight energy-saving, motion performance or stability under various scenarios. Finally, the controller is validated using a high-fidelity simulator called veDYNA.
Keywords: over-actuated electric vehicle; wheel torque distribution; integrated motion control; energy efficiency optimisation; model predictive control.
Design of nonlinear hierarchical controller for intake manifold pressure and boost pressure of turbocharged gasoline engine
by Hu Yunfeng, Wang Yaohan, Gong Xun, Gao Jinwu, Zhao Jinghua
Abstract: Precise tracking control of airpath systems, including intake manifold pressure and boost pressure, is key to ensuring the performance of turbocharged gasoline engines. Aiming at the above objective, we propose a nonlinear hierarchical controller to address the nonlinear and coupling characteristics of airpath systems in this paper. First, a control-oriented airpath model is obtained based on the working principle of a turbocharged gasoline engine. Second, the upper nonlinear controller is deduced in the framework of triple-step control method, whose asymptotic stability is guaranteed by linear system theory. Third, the lower controller performs a throttle-opening transformation, and a turbine speed tracking controller to achieve the value calculated by the upper controller. Specifically, the throttle-opening area is converted into a throttle-opening position by MAP (lookup tables), and a nonlinear observer-based turbine speed controller is obtained to address the unknown disturbance. Then, the actual input controls consisting of the throttle-opening position, and the wastegate opening position are obtained. Finally, the tracking performance and robustness of the proposed controller are verified by co-simulation using AMESim and Simulink.
Keywords: turbocharged gasoline engine; hierarchical control; nonlinear control; asymptotic stability; intake manifold pressure; boost pressure.
Temperature prediction and winding temperature measurement of a solenoid valve
by Yanyu Liu, Junqiang Xi, Fei Meng
Abstract: It is difficult to measure the temperature of solenoid valve windings in
an automatic transmission with high precision. Distributed optical fibre sensing
technology was used to measure the temperature of solenoid valve windings in this
study. The finite element method was also used to establish an electromagnetic-
thermal-mechanical coupling model describing the temperature of the solenoid
valve. Bidirectional coupling between the electromagnetic field and temperature,
and dynamic changes in material properties with temperature, are considered in
the model presented here. The simulation presented here is a closer representation
of an actual solenoid valve. The temperature distribution was calculated for
each component during operation. The simulated winding temperature and that
measured with the inverse resistance method in ideal conditions are compared with
the fibre optic temperature measurements. The results illustrate the feasibility and
accuracy of the method for measuring the temperature of small windings. Finally,
the reproducibility of the temperature measurement method was evaluated.
Keywords: solenoid valve; distributed optical fiber sensing technology; multi-physics coupling; winding temperature measurement.
Investigation into transmission radiated noise during the acceleration of electric buses based on response surface methodology
by Yong Chen, Ningning Qiu, Libin Zang, Changyin Wei, Guangxin Li, Lin Li
Abstract: Without the masking effect of engine noise, the transmission noise of the electric bus becomes prominent, which affects the NVH (Noise, Vibration, and Harshness) of the whole vehicle state. In this study, noise sources of 4-speed automated mechanical transmission of a pure electric bus were identified and optimised. The vehicle noise test under the acceleration condition is carried out. The test results show that the third-gear acceleration noise is more prominent than the others. Subsequently, the radiation noise model of the transmission is established by using the BEM (Boundary Element Method) and revised by the noise test under the acceleration condition. The gear lead crown and involute modifications of the shifting gear pair of the third-gear were selected as design variables based on Response Surface Methodology (RSM). The relationships between the design variables and the objective function were established. Finally, RSM is applied to optimise the transmission radiation noise transmission. The gear lead crown and involute modifications of shifting gears of the third-gear were selected as 2
Keywords: electric bus; the gearbox; the radiation noise; response surface method; order analysis; NVH; powertrain system; simulation.
Analysis of a passive scissor-like structure isolator with quasi-zero stiffness for a seating system vibration-isolation application
by Linchuan Guo, Axconny Khiua, Rang-lin Fan, Xu Wang
Abstract: It is widely known that vibration is a mechanical motion phenomenon where a mass point oscillates around an equilibrium point. Vibrations are a source of discomfort and are extremely harmful to vehicle drivers and passengers. The motivations of this research are to develop an innovative vehicle seating suspension system to isolate vibrations transmitted to vehicle drivers and passengers and to improve ride comfort to ensure that their health is not negatively impacted and to improve the working efficiency of the driver. An innovative design of a passive multi-degree-of-freedom vibration isolator is presented in a truck seat suspension system where a Stewart platform configuration with a six-degree-of-freedom (6-DOF) isolation system is used rather than the traditional Stewart platform. A scissor-like structure (SLS) is used as one of the supporting legs to provide a nonlinear system with quasi-zero stiffness. Vibration is effectively attenuated without a loss of the systems load capacity. The effects of structural parameters in the proposed system are studied to determine how to adjust the parameters to achieve better vibration-isolation performance. The results reveal that a SLS supporting leg with a small assembly angle, more layers, a shorter link length and less spring stiffness has led to better vibration isolation and higher system stability than the conventional baseline supporting structure.
Keywords: passive isolator; six degrees of freedom; vibration isolation; truck seats; seating suspension system; nonlinear stiffness; scissor-like structure; quasi-zero stiffness.
Active synchronising control of dual-mode coupling transmission for electric vehicles
by Lipeng Zhang, Xiaobin Guo, Liuquan Yang, Yunao Peng, Bingnan Qi
Abstract: Since the drive motor is more precise than the internal combustion engine in speed and torque adjustment, the clutches could be removed from an automated manual transmission (AMT) developed for electric vehicles. However, the synchroniser is reserved to adjust the residual speed and angle difference between the target gear and the engagement sleeve, which can improve the reliability of the transmission by avoiding significant wear and tear. Since the rotation angle of the drive motor can be precisely controlled, it offers a possibility to remove synchronisers and only rely on the motor to achieve the speed and angle synchronisation. In this paper, an active synchronisation control tactic is devised for a novel two-speed AMT named dual-mode coupling transmission. A speed-current double-closed-loop controller for regulating the drive motors speed is constructed, and a sliding mode observer is developed for the estimation of the state feedback information. And an odd-even tooth strategy based on particle swarm optimisation is designed to reduce the angle difference. The gear shift of the actuator adopts simple PID control. The proposed control strategy is validated by a series of simulation comparison. Furthermore, the feasibility of replacing the synchronisers with engagement sleeves and only relying on the active synchronisation control of the motor is analysed. This study illustrates that the active synchronisation control can reduce the reliance on the synchroniser to a large degree, and ensure the shift quality while reducing synchroniser wear, but the shift impact is still large after canceling the synchroniser rings, so the engagement sleeve structure and actuator control strategy must be optimised before replacing the synchroniser.
Keywords: electric vehicle; dual-mode coupling transmission; active synchronisation; shift control; odd-even tooth.
Special Issue on: Safety and Standards for Connected and Autonomous Vehicles
Coordinated torque vectoring control and path-following of autonomous vehicles with sideslip angle estimation
by Lin Zhang, Wei Pan, Qin Li, Haobo Sun, Nian Wang
Abstract: This paper proposes a coordinated control strategy that considers torque vectoring control and path-following system for autonomous vehicles with four in-wheel motors, while a state observer is designed to obtain some core vehicle states. Firstly, a non-linear vehicle state observer based on the UniTire tyre model is proposed to estimate longitudinal and lateral speed. Then the sideslip angle and tyre slip ratio can be obtained. Secondly, a lateral and longitudinal path-following algorithm using the driver model based on optimal preview theory and PI (proportion integral) controller is established. For the vehicle safety control of autonomous driving, a layered control scheme is proposed, in which the upper layer employs an adaptive second-order sliding mode controller to get additional yaw moment. The lower layer adopts an optimal moment distribution strategy to calculate the output torque of each motor considering the additional yaw torque control error, tyre workload usage, and the driver's longitudinal demand torque. Finally, simulation test results prove that the proposed state observation and coordinated control algorithm is valid.
Keywords: autonomous vehicles; torque vectoring control; path-following; sideslip angle estimation; in-wheel motors.
Action intention recognition of cars and bicycles in intersections
by Cristofer Englund
Abstract: Action intention recognition is becoming increasingly important in the road vehicle automation domain. Autonomous vehicles must be aware of their surroundings if we are to build safe and efficient transport systems. This paper presents a method for predicting the action intentions of road users based on sensors in the road infrastructure. The scenarios used for demonstration are recorded on two different public road sections. The first scenario includes bicyclists and the second includes cars that are driving in a road approaching an intersection where they are either leaving or continuing straight. A 3D camera-based data acquisition system is used to collect trajectories of the road users that are used as input for models trained to predict the action intention of the road users. The proposed system enables future connected and automated vehicles to receive collision warnings from an infrastructure-based sensor system well in advance to enable better planning.
Keywords: intention recognition; random forest; data mining; traffic behaviour modelling; variable selection.
Special Issue on: Revisiting Vehicle Dynamics and Control for Electrified and Autonomous Vehicles
Optimised robust path-following control of autonomous vehicles with pole constraints
by Yixiao Liang, Yinong Li, Amir Khajepour, Ling Zheng
Abstract: This paper presents a robust output-feedback guaranteed-cost control strategy for the path-following control of autonomous vehicles. First, the model of vehicle dynamics and path-following is established, which takes the uncertainties of cornering stiffness into account. Then, to deal with such uncertainties and improve the transient performance, a robust guaranteed-cost controller is introduced with the regional pole constraint ability. Considering that it is expensive and difficult to measure the side slip angle accurately, the proposed controller uses an output-feedback scheme without side slip angle information. Moreover, the particle swarm optimisation algorithm is selected to optimise the performance index of the guaranteed-cost controller such that the priorities among different objectives can be decided reasonably. Simulation results demonstrate the effectiveness of the proposed controller and its advantages over previous studies in the presence of parameter uncertainties.
Keywords: autonomous vehicle; path-following control; robust guaranteed-cost control; output-feedback control; particle swarm optimisation.