International Journal of Vehicle Systems Modelling and Testing (13 papers in press)
Simulation of a distance estimator for battery electric vehicles
by Chew Kuew Wai, Yong Yew Rong, Stella Morris
Abstract: Battery Electric Vehicles (BEV) are a promising candidate in reducing air pollution and fossil fuel dependencies. It is a growing market for the automobile manufacturers. Although there are many advantages of driving a BEV, it is still not widely accepted in the market owing to the limited driving range. Other than just improving the technologies that drive the vehicle, an additional range estimation system can calm the range anxiety‟ caused by the limited range of BEVs. Merely predicting the range based on the state of charge of the battery, the average driving speed, and the average power consumption is inadequate. This paper proposes a new range estimator, the dynamic range estimator, which also takes into account the driving behaviour, in addition to the slopes of the trip for its energy estimation. The driving behaviour is obtained based on the response to speed error and the time delay between throttle pedal and brake pedal switching. In this way, the driving behaviour is a fixed response for any driving speeds on the same route, thus allowing the energy consumption to be compared for different speeds.
Keywords: Matlab-Simulink; stateflow; distance estimator; battery electric vehicle; control system; vehicle dynamic; vehicle systems modelling; range anxiety; limited driving range; driving behaviour; energy estimation.
Evaluation of velocity and curvature dependence for roadgrip measured by low lateral slip
by Johan Casselgren, Sara Rosendahl, Niclas Engstrom, Ulrika Gronlund
Abstract: Roadgrip is a important parameter for vehicle testing and road maintenance. Therefore an evaluation of the velocity and curvature effects on roadgrip measurement was performed on asphalt roads and on two ice tracks using the continuous roadgrip apparatus RT3 Curve. The aim was to find suitable driving patterns for measurements on public roads and test tracks to ensure the repeatability of roadgrip measurements. During the evaluation it was concluded that in order to achieve a reliable roadgrip value, regardless of road conditions, the radius of curvature should not be less than 20 m. The velocity dependency of the RT3 Curve is different for the two road conditions, with the measurements on ice being much more sensitive to velocity changes than the measurements on the dry asphalt.
Keywords: friction; roadgrip; velocity dependence; slip angle; tyres; RT3 Curve.
Adaptive optimal control for integrated active front steering and direct yaw moment based on approximate dynamic programming
by Zhi-Jun Fu, Bin Li
Abstract: In this paper, a novel adaptive optimal control algorithm based on the approximate dynamic programming (ADP) approach is proposed for integrated active front steering (AFS) and direct yaw moment control (DYC). The corrective yaw moment and active steering angle are generated online without knowing the system dynamics, which is realised by using a neural network (NN) identifier to identify the unknown system dynamics and a critical NN to calculate the optimal control action, respectively. Control commands are executed via active steering angle on front wheels and proper brake torque distribution on the effective wheels. Computer simulations under three different driving manoeuvres, e.g. lane change manoeuvre, step steer manoeuvre and sine with dwell manoeuvre, are carried out to evaluate the proposed control method. Simulation results show that the proposed ADP-based control method demonstrates improved tracking performance in terms of enhancing vehicle handling and stability performance when encountering the varying longitudinal velocity, uncertain cornering stiffness, and the different road/tyre friction coefficients. Model-free and self-adaptive properties of the proposed method provide a new solution to vehicle stability controller design instead of the commonly used model-based methods.
Keywords: approximate dynamic programming; vehicle stability control; active front steering; direct yaw moment control; optimal tracking control.
Theoretical and experimental analytical study of powertrain system by hardware-in-the-loop test bench for electric vehicles
by Yong Li, Hongtao Xue, Haobin Jiang, Xing Xu
Abstract: Hybrid Energy Storage System (HESS) has been a promising technology in Electric Vehicles (EVs) to prolong the lifespan of lithium-ion batteries with the help of an ultra-capacitor. The powertrain system in EVs delivers the energy from the HESS to the wheels, during which the energy transforms between electrical and mechanical energy. The powertrain system determines the energy conversion efficiency of the HESS. Necessary investigation on the powertrain system should be done before further study on the characteristics of HESS. In order to deeply study the powertrain system, the dynamic model, which includes the traction motor, CVT and flywheel, is established and validated both in Psim and Matlab/Simulink software. NYCC and HWFET drive cycle are employed to operate as the reference speed of the traction motor. The speed control system of traction motor is modelled. The control strategy of the traction motor of the powertrain system is verified in a virtual vehicular environment. Simulation results illustrate that the fuzzy-PI control method is better in dynamic and static performance than single PI control. The control approach is implemented on a dSPACE-based hardware-in-the-loop test bench for real-time control. Experimental data demonstrates the velocity trajectory of the aforementioned drive cycles is exactly tracked. The transmission efficiency of the powertrain system and harvested energy during regenerative braking is investigated on the test bench. The work in this paper provides a solid foundation for further study on the power split of HESS.
Keywords: electric vehicle; hybrid energy storage system; powertrain; fuzzy-PI controller; hardware-in-the-loop.
An optimal robust controller for active trailer differential braking systems of car-trailer combinations
by Eungkil Lee, Yuping He, Saurabh Kapoor, Tushita Sikder
Abstract: This paper presents an optimal robust controller for active trailer differential braking (ATDB) systems for car-trailer (CT) combinations. To increase the safety of CT combinations, various active safety systems, e.g., ATDB, were proposed. Especially, controllers based on the linear quadratic regulator (LQR) technique have been explored for ATDB systems. In these LQR controller designs, vehicle forward speed, trailer payload, road conditions, etc., were assumed as constants. In reality, a CT combination is frequently confronted with variations of operating conditions, e.g., vehicle forward speed, and vehicle parameters, such as trailer payload. Lateral dynamic analysis of CT combinations with the LQR-based ATDB indicates that disturbances of operating conditions and vehicle parameters impose significant impacts on the lateral stability of these vehicles. This motivates the investigation into robust controller designs, which minimise the negative impacts of such parameter uncertainties on the directional performance of CT combinations. A model-based ATDB controller is designed using the μ synthesis technique. Generally, the tuning of weighting functions for the robust controllers is implemented using the trial and error method, and the design process is tedious and time-consuming. A new method using a Genetic Algorithm (GA) for tuning the weighting function parameters is presented. In the weighting function parameters tuning process with the GA, the lateral stability is emphasised and the path-following capability is considered. Numerical simulation results confirm the validity of the proposed ATDB controller.
Keywords: optimal robust controller; mu synthesis; model-based controller design; active trailer differential braking; lateral stability; car-trailer combinations.
Methodology for developing a neural network leaf spring model
by Kat Cor-Jacques, Jennifer Johrendt, Pieter Els
Abstract: This paper describes the development of a neural network that is able to emulate the vertical force-displacement behaviour of a leaf spring. Special emphasis is placed on aspects that affect the predictive capability of a neural network, such as type, structure, inputs and ability to generalise. These aspects are investigated in order to enable the effective use of it to model leaf spring behaviour. The results show that with the correct selection of inputs and network architecture, the neural networks ability to generalise can be improved and also reduce the required training data. The resulting 2-15-1 feed forward neural network is shown to generalise well and requires minimal data to be trained. Experimental data was used to train and validate the network. The methodology followed is not limited to the application of leaf springs only but should apply to various other applications, especially ones with similar nonlinear characteristics.
Keywords: leaf spring modelling; multi-leaf spring; neural networks; generalisation; experimental training data; experimental validation.
Validating power management strategies for hybrid sport motorcycles: a virtual prototyping approach
by Fabio Maran, Andrea De Simoi, Alessandro Beghi, Mattia Bruschetta
Abstract: In this paper, we consider the problem of assessing the performance of different power management strategies for a hybrid, 125cc sport motorbike. The electrical machine is used to obtain a torque boost during acceleration, with reduced emissions. Being a sport motorcycle, the impact of the hybridisation on performance in terms of handling has to be carefully evaluated. To this aim, a virtual environment has been realised, which allows to describe in detail the vehicle dynamics, as well as the characteristics of the hybrid power train. The simulation environment is completed by a virtual rider and a tool for building test circuits. The virtual environment is used to evaluate two different power management strategies, based on a standard heuristic and on torque-split optimal-control strategies, respectively. Results of simulations on a virtual track and of field tests are included.
Keywords: hybrid motorcycles; virtual rider; dynamic simulation; optimal control; energy management.
Sensitivity analysis of truck tyre hydroplaning speed using FEA-SPH model
by Zeinab El-Sayegh, Moustafa El-Gindy
Abstract: The hydroplaning phenomenon is a complex multi-physics problem that may affect any vehicle under wet road conditions. It is crucial to understand the hydroplaning phenomenon to improve passengers' safety on highways. This paper focuses on studying the hydroplaning of different truck tyres. The study includes the effect of inflation pressure, load, tread depth and water film thickness on hydroplaning speed. The tyres used in this study are Goodyear's off-road RHD 315/80R22.5 tyre and the UOIT FEA Michelin XOne Line Energy T 445/50R22.5 tyre. The analysis is performed using an FEA code named Pam-Crash from ESI Group. Water is modelled using the Murnaghan equation of state and SPH (Smooth Particle Hydrodynamics) method. The simulation results are validated against Horne's equation for truck tyres. An empirical equation is developed to include various tyre parameters.
Keywords: smooth particle hydrodynamics; hydroplaning; truck tyres; Pam-Crash; finite element analysis.
Truck tyre-terrain interaction modelling and testing: literature survey
by Zeinab El-Sayegh, Moustafa El-Gindy, Inge Johansson, Fredrik Öijer
Abstract: The interaction between tyre and terrain is the primary factor affecting the efficiency of the ride. The terrain on which the vehicle operates can range between dry or wet road to soil or clayey, depending on the vehicle application whether it is off-road or on-road. The terrain properties affect the vehicle ride significantly, and thus it is highly important to investigate this aspect. This paper focuses on studying the tyre-terrain interaction from several aspects. The truck tyres used in this study were previously modelled and validated by previous research. The terrains used are modelled in a virtual performance software Pam-Crash. The terrains include the hard surface (road); soils such as sand and clayey; snow; and water. The tyre-terrain interaction is modelled in Pam-Crash using contact definition, and several parameters are collected. The hydroplaning speed of the tyre is studied under different conditions of inflation pressure, vertical load, and water depth. The rolling resistance over several terrains is computed and compared. The soil mixing/layering concept is presented and investigated. This work is a preliminary step for an expanded investigation that will be applied during this research.
Keywords: truck tyre; tyre-terrain interaction; smoothed-particle hydrodynamics; finite element analysis; soil modelling and calibration; hydroplaning; Matlab/Simulink.
Aerodynamic analysis of an active rear split spoiler for improving lateral stability of high-speed vehicles
by Divya Teja Ayyagari, Yuping He
Abstract: This paper examines an active rear split spoiler designed for improving lateral stability of high-speed vehicles under high lateral acceleration (high-g) scenarios, such as a tight cornering manoeuvre at high speeds. Downforces produced by the spoiler can enhance the lateral stability of the vehicle under a high-g cornering manoeuvre. On the other hand, the spoiler may introduce additional drags on the vehicle. Aerodynamic analysis and wind tunnel testing are conducted to evaluate the dynamic effects of the active spoiler on a high-speed car. The downforce and drag, as well as their relationship are investigated using CFD simulations of the car with the active rear split spoiler at different spoiler angle of attack and at different speeds. Then, the achieved CFD simulation results are compared with the experimental data derived from the wind tunnel on the physical car and the spoiler prototype. The observations and findings achieved from the study may provide valuable guidelines for developing active aerodynamic control systems to increase safety of high-speed vehicles.
Keywords: aerodynamic analysis; CFD simulations; active rear split spoilers; lateral stability; high-speed vehicles.
The effect of swingarm stiffness on motorcycle stability: experimental measurements and numerical simulations
by Luca Taraborrelli, Valerio Favaron, Alberto Doria
Abstract: This paper focuses on the effect of swingarm deformability on motorcycle stability and in particular on the weave mode. Multibody models for the analysis of stability and handling of single track vehicles require a lumped element representation of the deformability of the critical structural elements of the vehicle. The twist axis method is used to identify lumped stiffness and damping elements able to represent bending and torsion deformability of the swingarm. Experimental tests and identification results dealing with two different swingarms are presented. The identified lumped stiffness and damping elements are implemented in a multibody code and some numerical stability analyses are carried out. Calculated results show that swingarm deformability has a small effect on the stability of super sport motorcycles, whereas the stability of the weave mode of enduro motorcycles is affected by swingarm deformability in a specific range of speeds.
Keywords: motorcycle; swingarm; weave; stability; twist axis; identification.
Development of a rolling truck tyre model using an automatic model regeneration algorithm
by Shahram Shokouhfar, Subhash Rakheja, Moustafa El-Gindy
Abstract: A three-dimensional finite element model of a rolling radial-ply truck tyre is developed to predict its vertical and cornering properties at relatively high speeds. The model includes a detailed representation of the tyre complex geometry and multi-layered composite structure including the carcass and belt plies, bead fillers and tread. LS-DYNA, a nonlinear finite element code, is used as the simulation tool. An algorithm is developed for efficient formulation of the model for parametric analyses. The validity of the proposed tyre model is demonstrated by comparing the predicted load-deflection, cornering and free vertical vibration characteristics with the reported experimental data. The simulation results revealed robust behaviour of the tyre model up to rolling speeds of 100 km/h. The verified tyre model is subsequently employed to study the influences of various operating parameters, namely, the inflation pressure, vertical load, rolling speed and road friction on the tyre vertical and cornering properties.
Keywords: rolling truck tyre models; multi-layered tyre structure; vertical tyre properties; cornering properties; parametric studies; finite element method; FEM; LS-DYNA; automatic model regeneration; truck tyres; tyre modelling; radial-ply tyres; carcass plies; belt plies; bead fillers; tyre tread; simulation; rolling speed; load deflection; free vertical vibration; tyre inflation pressure; vertical load; road friction; radial tyres.
Special Issue on: Modelling and Optimisation of Kinematics and Kinetics of Off-Road Vehicle Mobility and Performance by Artificial Intelligence
Path-planning in autonomous electric vehicles using nonlinear state estimation and behaviour-based controllers
by N. Muthukumar, G. Saravanakumar, Seshadhri Srinivasan, B. Subathra, K. Ramkumar
Abstract: Autonomous vehicle navigation in an unknown environment is a challenging task. This investigation presents two algorithms for autonomous vehicle navigation in unknown environments with obstacles. Basic building blocks of the path-planning algorithms are the behaviour-based controller and nonlinear state estimator. Measurements from sensors mounted on the vehicle are used as the input to the state estimator, whereas the estimated position of the vehicle with respect to the obstacle is the output. The estimate is then used to decide the possible control action from a family of behaviour-based controllers for navigating the vehicle. The first path-planning algorithm uses the Extended Kalman Filter (EKF) for estimating the vehicle position using measurements on obstacle position. The second path-planning algorithm uses the Unscented Kalman Filter (UKF) to estimate the vehicle position. Our results indicate that UKF-based path-planning algorithm performs better than the EKF-based algorithm in terms of both performance and fuel consumption. This is indicated by a 9% reduction of the control effort. Path-planning algorithms presented in this investigation can be used to build reliable autonomous vehicle navigation systems.
Keywords: autonomous vehicle, behaviour-based controller, unscented
Kalman filter, extended Kalman filter, path-planning, obstacle avoidance