This paper introduces a Hybrid Electric Vehicle (HEV) with eAWD capabilities via the use of a traditional Series-Parallel hybrid transaxle at the front axle and an electric Rear Axle Drive (eRAD) unit at the rear axle. Such a vehicle requires proper wheel torque allocation to the front and rear axles in order to meet the driver demands. A model of the drivetrain is developed using Bond Graphs and is used in co-simulation with a vehicle model from the CarSim software suite for validation purposes. A longitudinal slip ratio control architecture is proposed which allocates slip ratio to the front and real axles via a simple optimization algorithm. The Youla parametrization technique is used to develop robust controllers to track the optimal slip targets generated by the slip ratio optimization algorithm. The proposed control system offers a unified approach to longitudinal vehicle control under both traction and braking events under any road surface condition. It is shown in simulation that the proposed control system can properly allocate slip ratio to the front and rear axles such that tires remain below their force saturation limits while vehicle acceleration/braking is maximized while on a low friction road surface.
- Dynamic Systems and Control Division
Optimal Longitudinal Slip Ratio Allocation and Control of a Hybrid Electric Vehicle With eAWD Capabilities
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Velazquez Alcantar, J, Assadian, F, Kuang, M, & Tseng, E. "Optimal Longitudinal Slip Ratio Allocation and Control of a Hybrid Electric Vehicle With eAWD Capabilities." Proceedings of the ASME 2016 Dynamic Systems and Control Conference. Volume 2: Mechatronics; Mechatronics and Controls in Advanced Manufacturing; Modeling and Control of Automotive Systems and Combustion Engines; Modeling and Validation; Motion and Vibration Control Applications; Multi-Agent and Networked Systems; Path Planning and Motion Control; Robot Manipulators; Sensors and Actuators; Tracking Control Systems; Uncertain Systems and Robustness; Unmanned, Ground and Surface Robotics; Vehicle Dynamic Controls; Vehicle Dynamics and Traffic Control. Minneapolis, Minnesota, USA. October 12–14, 2016. V002T30A002. ASME. https://doi.org/10.1115/DSCC2016-9629
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