An agent-based integrated control framework is proposed to organize the active steering, active driveline, active brake, and anti-lock braking-acceleration slip regulation controllers, which traditionally have been relatively independent. Analysis is made of the characteristics of vehicle-handling dynamics, the functions of the individual controllers, and their interrelationships. A coordination mechanism is employed to manage interdependences and conflicts among the subcontrollers, so as to improve the flexibility, adaptability, and robustness of the global control system. The trade-off between yaw rate tracking, lateral stability, and longitudinal acceleration tracking is considered in the coordination. The control subsystems and the agent-based integrated control architecture are implemented in MATLAB/ Simulink to study the vehicle-handling capability under critical manoeuvring conditions. Simulation results show that the proposed intelligent and flexible control framework is predominant in organizing the subsystems, and could provide better performance than the stand-alone controllers for the vehicle longitudinal and lateral motion.

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This paper presents a novel active roll control algorithm for vehicle hydraulic active stabilizer bar system. The mechanical structure and control scheme of hydraulic active stabilizer bar system is detailed. The anti-roll torque controller is designed with “Proportional-Integral-Differential (PID) + feedforward” algorithm to calculate the total anti-roll torque. A lateral acceleration gain and roll rate damping are added into “PID + feedforward” controller, which can improve vehicle roll dynamic response. The torque distributor is introduced based on fuzzy–PID algorithm to distribute the anti-roll torque of front and rear stabilizer bar dynamically, which can improve vehicle yaw dynamics response. The actuator controller is used for realizing the closed-loop control of the actuators displacement and generating the accurate anti-roll torque. The hardware-in-the-loop simulation platform is established based on AutoBox and active stabilizer bar actuators. The hardware-in-the-loop experiment is carried out under typical maneuvers. Experimental results show that the proposed control algorithm improves the vehicle roll and yaw dynamics response, which can enhance the vehicle roll stability, yaw stability, and ride comfort.

Since the control of brake pressure has a significant impact on regenerative braking performance of electric vehicles, a novel combined brake pressure control algorithm based on two high-speed on-off valves is developed to improve the precision and timeliness of pressure tracking for the regenerative braking system of electric commercial trucks in this paper. First, a comprehensive mathematical model of the valve control system is built up which is composed of several sub-models and verified by experiments. Second, a PID controller with pulse width modulation (PWM) and a fuzzy controller with cooperative PWM are separately adopted in the proposed combined control algorithm to substitute for the traditional PWM approach. Moreover, through the numerical simulation studies, better control performance is obtained in MATLAB/Simulink on the basis of the built models. Finally, the experimental tests under various typical braking pressure input signals are carried out to verify the simulation results. The comparison between the simulation and experimental results fully demonstrates that the proposed control algorithm is feasible and the dynamic performance of this combined valve control algorithm is considerably improved compared with the conventional PID control algorithm. INDEX TERMS High-speed on-off valve, regenerative braking control, pressure tracking, fuzzy control, simulation, experimental test.

This study aims to develop a two-layer mass-adaptive control framework to improve the hill start assist performance of commercial vehicles equipped with an electronic parking brake system. In the first layer, the desired pressure of the hill start assist control is proposed, then a logic threshold control method is employed to track the time-varying desired pressure. Due to the frequently changing load of the commercial vehicles, the second layer is utilized to estimate the vehicle mass online. The proposed mass-adaptive control method is evaluated via a co-simulation platform involving MATLAB/Simulink, TruckSim and AMESim, and is compared with a one-layer scheme without mass estimation. Finally, we further demonstrate the feasibility and robustness of the two-layer mass-adaptive hill start assist framework in vehicle experiments.

Aiming at the problem of mass estimation for commercial vehicle, a two-layer structure mass estimation algorithm was proposed. The first layer was the grade estimation algorithm based on recursive least squares method and the second layer was a mass estimation algorithm using the extended Kalman filter. The estimated grade was introduced as the observation quantity of the second layer. The influence of the suspension deformation on grade estimation was considered in the first layer algorithm, which was corrected in real time according to the mass and road grade estimated by the second layer algorithm. The proposed estimation algorithm was validated via a co-simulation platform involving TruckSim and MATLAB/Simulink. Finally, a road test was carried out, and the evaluation method using the root mean square error was proposed. According to the test, the average value of the root mean square error reduces from 871.65 to 772.52, grade estimation is more accurate, and the convergence speed of mass estimation is faster, compared with estimation results of the extended Kalman filter method.

The engagement control of an automatic mechanical transmission (AMT) clutch during the hill start of a heavy-duty vehicle has a significant impact on the comfort, safety and service life of the vehicle. However, the control effect of a traditional control strategy can be easily affected by interference (clutch wear, temperature). Therefore, this paper proposes a two-layer structure control strategy based on an AMT clutch automatic actuator with the clutch engagement speed as the control target. First, the clutch automatic actuator is designed and the governing characteristics of the diesel engine and the control characteristics of the solenoid valve are studied. Second, a logic threshold control method and PID control method are adopted in the proposed two-layer structure control method. Moreover, the robustness of the proposed control algorithm is validated by a co-simulation platform (TruckSim, MATLAB/Simulink). Finally, experimental research under different slopes (13% and 22%) is carried out to verify the simulation results. The experimental results prove that compared with a single-layer control strategy, the two-layer control strategy proposed in this paper can shorten the start time by more than 10%, and reduce the vehicle start-up jerking by approximately 20%, which significantly improves the performance of the vehicle in the hill start process.

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