Abstract
There are various strategies of control demand distribution between frictional brake system and electric motors of an electric vehicle. However, influence of subsystem coordination on electric vehicle (EV) characteristics, such as stability of motion, braking performance, energy recuperation and energy losses, is still weak-investigated. Moreover, subsystem coordination depends strongly on dynamic performance of actuators and on the vehicle manoeuvre. The main research objective of the presented study is a simulation-based analysis of EV subsystem coordination under various driving manoeuvres. The engineering objective is a development and testing of the blending control strategy providing optimal EV characteristics. The work introduces the control system, which provides the coordination between a friction brake system and electric motors, and includes three levels: PI controller of vehicle dynamics control and demand correction, optimization-based control allocation with actuator and tyre friction constraints, low-level PI/PID actuator control. The simulation analysis of the proposed control system has been carried out using the full vehicle simulator in IPG/Carmaker. Based on simulation analysis, the coordination weights for the control allocation were defined to reach optimal characteristics of vehicle motion and energy consumption / losses. The experimental investigation of proposed control system has been performed on the hardware-in-the-loop (HIL) test rig with the real friction brake system, emulators of electric motors and IPG/Carmaker vehicle simulator. The modelling covers three typical types of vehicle motion: straight-line braking, braking-in-turn and lateral motion based on “Sine with Dwell” test. Evaluation criteria for vehicle dynamics and stability of motion are (i) the braking distance, (ii) the root mean square error (RMSE) of yaw rate and (iii) the RMSE of sideslip angle. The measures for energy consumption and power losses are (i) the total amount of recuperated energy and (ii) the tyre energy dissipation. These criteria are investigated in respect to the blended operation of the friction brake system and electric motors. Thereby, obtained results demonstrate an influence of each subsystem on stability of motion, braking performance, energy recuperation and energy losses. Two variants of subsystem coordination are investigated using HIL test rig and compared. The first part of the article, having more theoretical significance, relates to coordination analysis and has been investigated by computational simulation. The second part of the paper covers the emulation of electric motors and vehicle dynamics and refers to an application of online optimization-based control allocation, which requires heavier computation time as compared with other techniques. The results proposed in this study leads to a novel EV brake blending strategy based on optimal control allocation with different subsystem coordination.
KEYWORDS – electric vehicle, control allocation, recuperation, hardware in the loop, subsystem coordination