International Journal of Vehicle Design (9 papers in press)
Novel design concept for an automotive proving ground supporting multilevel CAV development
by Adam Nyerges, Zsolt Szalay, Zoltan Hamar
Abstract: Technological changes usually bring new possibilities in everyday life. Thanks to the recent evolution in science and technology, road transport is going to change radically. Today's complex assistant systems help the human driver to manoeuvre the vehicle safely. In the near future, connected and highly automated vehicles will also appear on the road, in multiple transport modes. Higher vehicle automation levels rely on disruptive technologies that simply cannot be tested and approved in the currently used sustaining technologies format. As validation processes become more complicated they require a more specific and ever-changing test environment. Current autonomous vehicle test environments are developed around activities that mostly concentrate on an urban test area, while every single element of the new Hungarian automotive proving ground is dedicated to the testing and validation of connected and automated vehicles. This paper will discuss this complex and integrated design concept, illustrating the unique points that differentiate the new Hungarian test facility from that of a conventional vehicle test track as well as from other current autonomous vehicle testing areas.
Keywords: connected and automated vehicles; autonomous driving; self-driving vehicles; testing and validation; test track; proving ground; smart city; intelligent transport.
Mine car suspension parameter optimisation based on improved particle swarm optimisation and approximation model
by Jun Zhang, Xin Li, Duyou Liu
Abstract: A suspension parameter optimization method is proposed in this paper to improve mine car ride comfort. The most influential parameters on vehicle ride comfort are chosen as optimisation variables by analysing parameter sensitivity using a 7-degrees-of-freedom vehicle model. A simplified regression model based on the response surface method accelerates the optimisation process. An improved chaos particle swarm optimisation (ICPSO) approach is proposed based on standard particle swarm optimisation to optimise suspension parameters in the regression model. The ideal match of suspension parameters is obtained. Simulation results show that improved suspension parameters can greatly ensure the weighted root mean square acceleration and tyre dynamic loads; additionally, suspension dynamic deflections are limited within an allowable range. Test results reveal that the suspension multi-parameter optimisation method based on ICPSO can improve vehicle ride comfort. Therefore, this method can be used to guide future research and development of suspension systems.
Keywords: mine car ride comfort; suspension parameter optimisation; Particle swarm optimisation; approximation model.
Design and evaluation a passive inertial mass device for car suspension system
by Shuai Yang, Chuan Li
Abstract: A new adaptive nylon flywheel is proposed, which can achieve passive vibration control by generating variable equivalent mass. With changing rotational speed, the location of sliders in the slots changes, which leads to the creation of variable equivalent mass. Owing to the light weight and high strength of the nylon material, a higher changing ratio of equivalent mass can be achieved. To verify the performance of the adaptive nylon flywheel, the inverse screw system was applied. By using zero, impulse and sinusoidal input as road excitation, the proposed car suspension system is evaluated from riding comfort and tyre grip. Simulation results show the proposed suspension system provides better performance than traditional suspension system under most circumstances.
Keywords: inertial mass; passive; car suspension; adaptive flywheel.
Special Issue on: Recent Advances in Sensing Technology, Vehicle Control Systems and Tyre Design Considerations for Electric and Autonomous Vehicles
Vehicle longitudinal force estimation using adaptive neural network nonlinear observer
by Mourad Boufadene, Mohammed Belkheiri, Abdelhamid Rabhi, El Hajjaji Ahmed
Abstract: This paper presents an adaptive neural network (ANN) nonlinear observer to estimate the longitudinal tyre forces as well as the lateral speed, which is not measured on standard vehicles. The proposed ANN observer uses the longitudinal speed, yaw rate and the steering angle dynamics of the vehicle as measured states. It is used to estimate the states, and the longitudinal tyre forces, which are unknown dynamics, with high performance. The obtained simulation results show the effectiveness of the proposed neural network nonlinear observer.
Keywords: adaptive observer; adaptive neural network; radial basis function
approximation; nonlinear observer; vehicle force estimation; tyre forces
estimation; longitudinal vehicle force estimation.
Integrated control of AFS and DYC for in-wheel-motor electric vehicles based on operation region division
by Jianjun Hu, Zhihua Hu, Chunyun Fu, Fuqian Nan
Abstract: The integrated chassis control system can improve vehicle handling and stability effectively. This paper proposes an integrated control system based on operation region division of AFS and DYC for in-wheel-motor electric vehicles. The control system adopts a two-layer hierarchical control structure. The decision layer employs a modified sliding mode controller to calculate the required corrective yaw moment, and determines operating regions of the two subsystems based on the driving conditions (road adhesion coefficient, tyre load and wheel slip ratio). The execution layer generates the corrective steer angle and the driving/braking toques for the AFS and DYC subsystems respectively. Simulation results show that on the high-adhesion-coefficient road, the integrated control system appropriately adopts subsystems to improve handling, while attenuating the workload of barking system; on the slippery road, the integrated control system maintains vehicle stability and provides superior control performance to those resulting from the single systems.
Keywords: driving stability; AFS; DYC; yaw rate; hierarchical control; operation region division; lateral tyre force; Magic Formula; sliding mode control.
Pressure control of integrated electro-hydraulic braking system considering driver braking behaviour
by Hao Pan, Xuexun Guo, Xiaofei Pei, Daoyuan Sun
Abstract: This paper proposes a pressure controlling strategy for the Integrated Electro-Hydraulic Braking (IEHB) system when considering driver braking behaviour. Firstly, the representative feature parameters of braking behaviour are extracted from various vehicle data and clustered by manoeuvre characteristics. Seven brake pedal operation training libraries are self-learned adaptively by hidden Markov model for driver braking behaviour recognition. Then, a self-tuning function based on recognition results is proposed to adjust the PWM parameters of the PI controller for the motor and valve. Eventually, the hardware-in-loop results of IEHB system show the accuracy of braking behaviour recognition algorithm, and the feasibility of self-tuning control strategy. In addition, the effectiveness of pressure regulation for the IEHB system is verified.
Keywords: electro-hydraulic braking system; braking behaviour; hidden Markov model; pressure control; self-tuning PI.
Active steering control system for an independent wheel drive electric vehicle
by M.A. Khan, M.F. Aftab, E. Ahmad, Iljoong Youn
Abstract: This research presents an active steering control system (ASCS) for an independent wheel drive electric vehicle (EV). The ASCS will manoeuvre the independently actuated (IA) all-wheel drive (AWD) EV via coordinating the angular velocities of the four wheels plus active front steering (AFS). Owing to the physical and mechanical limitations of the steering input in conventional AFS, the differential speed between left and right wheels of an IA EV is used to generate the additional steering effects. The ASCS is designed using the linear model of the vehicle and is tested in simulations using the nonlinear vehicle model. The proposed ASCS is a combination of forward speed and yaw rate controllers, designed using the robust $H_infty$ control methodology. The effectiveness of the proposed control system is analysed by comparing the performance of an AWD IA EV with ASCS, a rear wheel drive (RWD) IA EV with ASCS, a vehicle with AFS only, and a vehicle with no controller. The simulations results using a high-fidelity vehicle model under different driving conditions and road disturbances, indicates that the proposed system can significantly improve the vehicle performance by tracking the desired yaw rate and speed.
Keywords: differential steering control; active front steering; electric vehicle; four wheel drive; nonlinear vehicle model; steering control; vehicle dynamics; yaw rate tracking.
A data-based lane departure warning algorithm using hidden Markov model
by Hongyu Zheng, Jian Zhou, Huaji Wang
Abstract: In order to improve the lane departure warning algorithm in vehicle lateral assistance strategy to avoid crashes, an effective approach based on the factors of driving behaviours is needed. Considering that steering events are the primary reason for lane departure, in this paper, a data-based departure warning algorithm is proposed using hidden Markov model (HMM) to detect the lane departure state. In HMM, the current steering event is the hidden state, and driving state information is the observed sequence. In addition, a further judgement strategy is made to distinguish the intentional lane departure from the unintentional lane departure before sending the warning signal to the driver. Finally, after selecting a reasonable time window in HMM, experiments are conducted on the test bench to compare the data-based algorithm and the time to lane Crossing algorithm. The experimental results indicate that the proposed algorithm has better performance on accuracy and sensitivity.
Keywords: lateral assistance system; lane departure warning; hidden Markov model; steering events; identification; time window; further judgement; time to lane crossing; comparison experiments; accuracy; sensitivity.
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.