Study on simulation and scheduling algorithm of CAN control for independently driving electric vehicle

Safety-critical applications such as the independently driving systems of electric vehicle （EV） require a high degree of reliability. The controller area network （CAN） is used extensively in the control sectors. A new real-time and reliable scheduling algorithm based on time-triggered scheduler with a focus on the CAN-based distributed control systems for independently driving EV is exploited. A distributed control network model for a dual-wheel independendy driving EV is established. The timing and reliabili- ty analysis in the worst case with the algorithm is used to evaluate the predictability and dependability and the simulation based on the algorithm with CANoe software is designed. The results indicate the algorithm is more predicable and dependable.

Simulation investigation of tractive energy conservation for a cornering rear-wheel-independent-drive electric vehicle through torque vectoring

Although electric vehicle fully exhibits its comparative merits of energy conservation and environmental friendliness, further improvement of its traction energy efficiency lacks comprehensive investigations in the past. In this paper, the effect of the torque vectoring on traction energy conservation during cornering for a rear-wheel-independent-drive electric vehicle is investigated.Firstly, turning resistance coefficient and energy conservation mechanism of torque vectoring are derived from the single track dynamic model. Next, an optimal torque vectoring control strategy based on genetic algorithm is proposed, with the consideration of the influence of the operation-point change of the in-wheel motors, to find out the best torque vectoring ratio offline. Finally,various simulation tests are conducted to validate the energy conservation effect after Simulink modelling. The results verify that though the optimization of the operating region of the motors is the main part for tractive energy conservation, the contribution of torque vectoring itself can reach up to 1.7% in some typical cases.

Driver Model-Based Fault-Tolerant Control of Independent Driving Electric Vehicle Suffering Steering Failure

This paper presents a fault-tolerant control(FTC)strategy for a four-wheel independent driving electric vehicle suffering steering failure.The method is based on the functional redundancy of driving and braking actuators to recover the vehicle’s steering ability.A dynamic vehicle model is derived with the function of four-wheel driving.A sliding mode controller with a combined sliding surface is employed as a motion controller,allowing the desired vehicle motion to be tracked by the adaptive drivermodel.An extended Kalman filter-based state estimator is adopted to virtually measure the sideslip anglewhile considering the nonlinear tire force.A new allocation strategy,involving two distribution modes of coordination,is designed.In addition,a weight coefficient adjustment strategy is implemented in optimal mode based on the lateral load transfer,thus improving the steering performance.Simulations are conducted to verify the proposed FTC algorithm.The results demonstrate that steering failure can be effectively covered by the functional redundancy of the driving/braking actuators.