This paper presents a robust fuzzy $H_{\infty }$ control strategy for improving vehicle lateral stability and handling performance through integration of direct yaw moment control system (DYC) and active front steering. Since vehicle lateral dynamics possesses inherent nonlinearities, the main objective is dedicated to deal with the nonlinear challenge in vehicle lateral dynamics by applying Takagi-Sugeno (T-S) fuzzy modeling approach. First, the nonlinear Brush tire dynamics and the nonlinear functions of longitudinal velocity are represented via a T-S fuzzy modeling technique, and vehicle parametric uncertainties are handled by the norm-bounded uncertainties. An uncertain nonlinear vehicle lateral dynamic T-S fuzzy model is then obtained with multi-fuzzy-rules. The resulting robust fuzzy $H_{\infty }$ state-feedback controller is designed with the parallel-distributed compensation strategy and premise variables, and solved via a set of linear matrix inequalities derived from Lyapunov asymptotic stability and quadratic $H_{\infty }$ performance. Simulations for two different maneuvers are implemented with a high-fidelity, CarSimⓇ, full-vehicle model to verify the effectiveness of the developed approach. It is confirmed from the results that the proposed controller can effectively preserve vehicle lateral stability and enhance yaw handling performance.

Improving Vehicle Handling Stability Based on Combined AFS and DYC System via Robust Takagi-Sugeno Fuzzy Control

This study presents an integrated multi-objective controller for electric vehicles ( EVs) to achieve four main control objectives concurrently, i.e. slip control in traction and braking, lateral st...

Model Predictive Control for integrated lateral stability, traction/braking control, and rollover prevention of electric vehicles

Clutch shift control is critical for efficient and high-performance transmission designs, including automatic, dual clutch, and hybrid transmissions. To ensure a smooth clutch to clutch shift, appropriate controls for two consecutive processes are critical. One is the precise coordination between the on-coming and off-going clutches, which requires the on-coming clutch to be filled and ready for engagement at the predetermined time (clutch fill). The other is the proper torque control during clutch engagement. In this paper, we will investigate the closed-loop “wet” clutch control enabled by a pressure sensor in the clutch chamber. The main challenges of the pressure-based “wet” clutch control lie in the complex nonlinear dynamics due to the interactions between the fluid and the mechanical systems, the ON/OFF behavior of the clutch assembly, the time-varying clutch loading condition, the required short time duration for a precise and robust clutch shift, and the lack of the displacement information. To enable precise and robust pressure-based control, this paper focuses on the following three aspects. First, a clutch dynamic model is constructed and validated, which precisely captures the system dynamics in a wide pressure range. Second, a sliding-mode controller is designed to achieve robust pressure control while avoiding the chattering effect. Finally, an observer is constructed to estimate the clutch piston motion, which is not only a necessary term in the nonlinear controller design but also a diagnosis tool for the clutch fill process. To validate the proposed methods, a transmission clutch fixture has been designed and built in the laboratory. The experimental results demonstrate the effectiveness and robustness of the proposed controller and observer.

Pressure-Based Clutch Control for Automotive Transmissions Using a Sliding-Mode Controller

For four wheel independent motor-drive electric vehicle, the vehicle longitudinal and lateral motion can be controlled by distributing the driving and regenerative braking torques of four wheel motors. To meet the driving command of driver and keep the vehicle lateral stability, a hierarchical control system is proposed in this paper. In the upper layer, a nonlinear model predictive control is implemented to solve the nonlinear multiinput multioutput, over-actuated problem. The controller is based on a nonlinear three degree-of-freedom model with nonlinear tire model, considering wheel slips as virtual control input. In the lower layer, the wheel slips are manipulated by a PID controller for generating driving and regenerative braking torques of the independent motors. This proposed controller is tested in a hardware-in-the-loop system with four typical maneuvers, which are constant velocity, accelerating, decelerating, and low road adhesion coefficient situations to show different driver command. The results show that the driver command of longitudinal and lateral motion control are both satisfied.

Coordinated Longitudinal and Lateral Motion Control for Four Wheel Independent Motor-Drive Electric Vehicle

Torque optimization control for electric vehicles with four in-wheel motors equipped with regenerative braking system

MPC-based yaw stability control in in-wheel-motored EV via active front steering and motor torque distribution

Nonlinear MPC-based slip control for electric vehicles with vehicle safety constraints

To improve the vehicle stability of an electric vehicle with four in-wheel motors, an integrated control scheme with active front wheel steering and direct yaw moment is proposed using a triple-step nonlinear method. The method handles the nonlinear tire characteristics explicitly and actualizes a decoupling control for the considered two-input two-output nonlinear system, in the sense that the closed-loop error dynamics evolve independently. The design procedure is formalized as a triple-step deduction, and the derived controller consists of three parts: steady-state-like control, feedforward control considering reference variations, and state-dependent error feedback control. Finally, the designed controller is evaluated in a realistic seven DOF vehicle model and results are satisfying.

Integrated control of in-wheel motor electric vehicles using a triple-step nonlinear method

For a novel type of automatic transmissions adopting clutch-to-clutch shift control technology with electro-hydraulic actuators, a clutch pressure observer method based on input-to-state stability (ISS) is proposed. Model uncertainties including steady state error and unmodelled dynamics are considered as additional disturbance inputs and the observer is designed in order that the error dynamics is input-to-state stable. Lookup tables, which are widely used to represent complex nonlinear characteristics of engine systems, appear in their original form in the designed reduced-order observer. The designed pressure observer is tested on an AMESim powertrain simulation model. Comparing with the sliding mode method, the designed pressure observer has the better performance.

Haiyan Zhao

Papers

MPC-based yaw stability control in in-wheel-motored EV via active front steering and motor torque distribution

Torque optimization control for electric vehicles with four in-wheel motors equipped with regenerative braking system

Nonlinear MPC-based slip control for electric vehicles with vehicle safety constraints

Integrated control of in-wheel motor electric vehicles using a triple-step nonlinear method

A Reduced-Order Nonlinear Clutch Pressure Observer for Automatic Transmission