Research On Slip Control System For Electric Vehicles With Four In-Wheel Motors

Electric Vehicles(EVs) with in-wheel motors have received much research interest nowadays due to their relatively simple drivetrain structure and flexible mode of actuation.Since the torque and angular velocity of the four in-wheel motors can be generated fast,and controlled precisely and independently, and the motors can work both on traction and braking mode, EVs with in-wheel motors provide a solid foundation for advanced slip control techniques. This paper mainly focuses on the research on slip control system for electric vehicles with four in-wheel motors. Compared with the conventional internal combustion engines(ICE) vehicles, the slip control system of EVs can effectively prevent the vehicle tyres from locking up when braking or spinning out when accelerating, thereby enhancing the directional stability and safety of the vehicle. However, the slip control system must control the four wheels precisely at the same time, so it makes the control problem so complex that normal algorithms can hardly meet the control requirements.This paper proposes a slip control system for EVs based on nonlinear model predictive control(nonlinear MPC) scheme. In order to ensure vehicle safety, the longitudinal slip of four wheels must be limited within the stable zone, which is considered as time-domain constraints of nonlinear MPC, and the stable zone varies with the road conditions. Due to motor physical limits, the driving/baking ability of motor is limited, so the actual motor torque can not exceed maximum output torque. And the maximum output torque is the function of motor angular velocity and battery voltage, so it is considered as timevarying constraints. And the objective function in this paper includes: good longitudinal acceleration and braking performance, preservation of driver comfort and lower power consumption. Besides, the slip control system must control the four wheels precisely at the same time, so it is a nonlinear constrained multi-objective optimization control problem.This paper utilizes nonlinear MPC to solve this problem, which can effectively solve this complex optimization control problems, and effectively deal with the constraints explicitly.A penalty term on the slack variables are also added to ensure that the state constraints do not cause infeasible problems. The proposed controller prevents the tyres from locking up while braking or spinning out while accelerating, by controlling the torque of each wheel to limit the longitudinal slip within the stable zone, and achieve a good longitudinal acceleration and braking performance by providing large longitudinal forces to each wheel under the premise of ensuring vehicle safety. In order to verify the effectiveness of the proposed controller, this paper builds a fifteen degrees of freedom(15DOF) high precision EV model in AMESim. And the good performance of the nonlinear MPC controller are verified by off-line simulations and rapid control prototyping experiments under several different typical maneuvers.The main contents and innovation points of this paper:1. This paper builds a fifteen degrees of freedom(15DOF) high precision EV model with four in-wheel motors in AMESim, and combining with the real vehicle data to complete the parameter matching and the analysis of system dynamics, to provide the basis for control system design.2. This paper designs a slip control system for EVs with four in-wheel motors,based on nonlinear MPC scheme. The control objectives include: vehicle safety, good acceleration and braking performance, as well as the preservation of driver comfort and lower power consumption. In order to ensure vehicle safety, wheel slip stable zone is considered as time-domain constraints of the nonlinear MPC. And the motor maximum output torque limitation is considered as time-varying constraints. In addition, a penalty term on the slack variables are also added to ensure that the state constraints do not cause infeasible problems. The effectiveness of the proposed slip control system is verified in the off-line co-simulation environment of AMESim and Simulink under several different typical maneuvers.3. Use particle swarm optimization(PSO) algorithm to solve nonlinear MPC optimization control problems, so as to improve the real time performance of nonlinear MPC.And a rapid control prototyping platform based on d SPACE is introduced to test and verify the real-time computational performance of the proposed controller. The experimental results show that the proposed controller is effective, and it also provides a basis for further engineering application.