Zong Changfu

Vehicle active front steering and yaw moment integrated control

An integrated control algorithm based on model predictive control (MPC) for vehicle active front steering (AFS) and yaw moment control integrated control (DYC) is proposed in this paper. Hierarchical integrated control structure is adopted in the algorithm. Design the model predictive controller and use the quadric programming method for tire force allocation. The algorithm is verified by the simulation. The results show that the algorithm can enhance the vehicle stability and is feasible.

Advanced Integrated Control Strategy Based on SBW and 4WS

This paper proposes a chassis integrated control system theoretically utilizing SBW system by using 4WS method to improve vehicle handling and stability. With the application of integrated SBW and 4WS strategy, this paper investigates the effectiveness of the proposed control system in enhancing vehicle handling and stability. Based on the 7 DOF vehicle dynamic models, the paper have proposed integrated control strategy for SBW and 4 WS including forward and feedback control methods in the four wheels (4WS). Two control methods are compared by simulation results and driver simulator test results. The simulation results indicated that 4WS for SBW can effectively improve the vehicle handling.

Vehicle state and road friction coefficient estimation based on double cubature Kalman filter

For the estimation problem of vehicle state and road adhesion coefficient in driving, the estimation algorithm of vehicle state and road adhesion coefficient were studied in this paper based on double cubature Kalman filter. The 3-DOF nonlinear vehicle estimation model with Dugoff tire model was established. The vehicle driving state estimator and tire-road friction coefficient estimator based on double cubature Kalman filter were designed. The estimators contact with each other in the process of estimation and forms a closed loop feedback to estimate the vehicle state and road adhesion coefficient timely and accurately. Selecting the typical working condition, the algorithm was verified by driving simulator experiments in the loop. The results showed that estimation algorithm based on double cubature Kalman filter can more accurately estimate the vehicle state and road adhesion coefficient than estimation algorithm based on extend Kalman filter.

The study of traction control system for Omni-directional electric vehicle

Traction control system is studied based on the Omni-directional vehicle which is built by our research group. The research mainly involves two aspects, vehicle state estimation and vehicle traction control logic design. Extended Kalman Estimation relying on multiple degrees of freedom vehicle model is used to estimate vehicle longitudinal speed, lateral speed, side slip angle, and yaw rate. Traction control system calculates tire slip ratios of four wheels according to the estimated vehicle velocity, and then traction control logic is designed by PID control. Simulations based on Carsim and Matlab/Simulink show that vehicle state estimation algorithm estimates vehicle speed, side slip angle and yaw rate effectively, and traction control logic can prevent wheel from excessive spinning using by the estimated slip ratio to improve vehicle acceleration performance and directional stability.

Research on Heavy Truck Rollover Prevention Based on LMI Robust Controller

This paper sets up a vehicle dynamic model which is used to determine rollover risk of heavy truck under various driving conditions. Using this real-time dynamic model, it proposes a new measure of performance for vehicle rollover prevention, the Load Transfer Ratio (LTR), and design the differential braking controller based on LMI robust control to prevent rollover occur. The paper also obtains the controller which can adopt the robustness to variations in vehicle speed. The simulation results show that the LMI controller is very effective in vehicle rollover prevention control.

Rollover prevention for heavy trucks using robust control

Heavy truck rollovers are dangerous and possibly fatal accidents. This paper discusses a robust control algorithm to improve the roll stability of heavy trucks. The controller minimizes the lateral load transfer (LTR) to reduce the rollover probability using differential braking. The paper also designs the robust controller which can adopt the robustness to variations in vehicle speed. The simulation results show that the robust controller is very effective in vehicle rollover prevention control of heavy trucks.

A control strategy of electronic braking system based on brake comfort

EBS offers considerable advantages to improve the braking performance of commercial vehicle. This paper proposes a control strategy of EBS, which is focused on the comfort assessment of vehicles. The road conditions are identified by the identification parameter, which is obtained when the slip-ratio reaches a certain point. The strategy is able to select the maximum deceleration, according to road conditions as well as the comfortable feeling of the drivers. The moving speed of the braking pedal is used to judge the drivers non-emergency brake intention. The braking force is distributed on the front axle and the rear axle ideally, with the axle load and the gravity position are taken into consideration. The performance of the strategy has been simulated. The results show that the strategy can identify the road condition effectively and make the driver feel comfortable during the brake process.

An Advanced Methodology for Rollover Warning of Heavy Duty Truck Based on Kalman Filter State Estimation

The rollover warning technology reported in this paper focuses on detection of heavy duty truck real-time rollover propensities. The paper suggests a new algorithm of rollover warning for heavy duty vehicle based on Kalman filter technology. Its feasibility for implementation in a heavy duty truck rollover threat detection system is demonstrated through vehicle dynamic simulation studies. The effectiveness of the rollover warning is validated by test data of heavy duty. It has been demonstrated that the proposed rollover warning system is very suitable for application in rollover risk assessment and warning.

A Real-Time Rollover Warning System for Heavy Duty Vehicle

This paper proposes a real-time rollover threat warning system (RWS) of heavy duty vehicle. The function of RWS is used to determine the rollover threat of heavy duty vehicle and warn the driver to adjust the operation during dangerous conditions. The paper suggests a new algorithm of rollover warning for heavy duty vehicle based on accurate PTR metric. The effectiveness of the RWS is validated by test data of heavy duty. The vehicle test results show that the RWS system is very suitable for application in rollover risk assessment and warning.

The design of rollover prevention system in heavy vehicles based on an robust method

This paper presents a novel approach for designing robust vehicle rollover prevention controllers. The control methodology is based on guaranteeing a set of linear matrix inequality (LMI) conditions, which results in controllers that are robust stable. An active braking control is used to decrease the rollover risk of heavy vehicles. The paper also obtains the controller which can adopt the robustness to variations in vehicle speed. The simulation results show that the LMI controller is very effective in vehicle rollover prevention control.