A systematic approach to modeling and control of vehicles is presented exploiting the flexibility of future four wheel drive electric vehicles. A control structure is developed consisting of a combined feedforward and feedback control to exploit the advantages of both model based predictive and robust model based feedback control. A reference model is used to translate driver demands to the control system in a physical compatible way. The feedforward control system is built on a quadratic optimal control problem relying on a simplified vehicle model and taking into account limitations in both driving torques and slip forces. The feedback control system uses an adaptive pole placement method to take into account strong nonlinear effects of vehicle dynamics and to reduce sensitivity to changing parameters and disturbances. To allow for a real-time implementation of both feedforward and feedback controller in a microcontroller models are simplified and all mathematical operations arising during solving the quadratic optimization problem or the adaptive pole placement problem are prepared symbolically to generate very compact equations. Verification of the control system is done in a first step by simulation with a 2D vehicle model using Matlab/Simulink. In a second step a complex 3D vehicle model containing realistic motor, suspension and steering systems is used to verify the function of the control system under more realistic conditions.
Modeling and control of a four wheel drive electric vehicle
2010
10 Seiten, 8 Bilder, 8 Quellen
Conference paper
Storage medium
English
European Patent Office | 2019
|European Patent Office | 2018
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