Abstract
Direct Yaw Moment Control (DYC) is an effective way to alter the behaviour of electric cars with independent drives. Controlling the torque applied to each wheel can improve the handling performance of a vehicle making it safer and faster on a race track. The state-of-the-art literature covers the comparison of various controllers (PID, LPV, LQR, SMC, etc.) using ISO manoeuvres. However, a more advanced comparison of the important characteristics of the controllers’ performance is lacking, such as the robustness of the controllers under changes in the vehicle model, steering behaviour, use of the friction circle, and, ultimately, lap time on a track. In this study, we have compared the controllers according to some of the aforementioned parameters on a modelled race car. Interestingly, best lap times are not provided by perfect neutral or close-to-neutral behaviour of the vehicle, but rather by allowing certain deviations from the target yaw rate. In addition, a modified Proportional Integral Derivative (PID) controller showed that its performance is comparable to other more complex control techniques such as Model Predictive Control (MPC).
Highlights
The irruption of electric technology in the automotive industry is setting a new and important milestone in automotive history
Many contributions have been proposed to the employment of different control methods for Direct Yaw Moment Control (DYC), especially in the last ten years, given the torque distribution freedom of electric powertrains with independent motors, and in some cases due to the advancements made in electronic differentials
This manuscript will perform a systematic comparison of the main control approaches (PID, Linear Quadratic Regulators (LQR), Sliding Mode Control (SMC), Model Predictive Control (MPC), and NMPC) and their performance is evaluated on two race tracks in this study
Summary
The irruption of electric technology in the automotive industry is setting a new and important milestone in automotive history. Linear Quadratic Regulators (LQR) are optimal controllers that balance the tracking performance of the state variables (minimization of the overall error of the yaw rate) with the actuation (commanded asymmetrical torque on the wheels). A comprehensive and systematic comparison of different control techniques for DYC is missing in the literature, to the knowledge of the authors This manuscript will perform a systematic comparison of the main control approaches (PID, LQR, SMC, MPC, and NMPC) and their performance is evaluated on two race tracks in this study. These studies have been performed using the IPG CarMaker software using an “expert driver model”, since a race car is being studied. A low centre of gravity, and small vehicle mass and inertia, in combination with high grip tyres, allows very good handling behaviour in terms of yaw rate response, at combined acceleration
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