Abstract

The water medium hydraulic retarder is the latest type of auxiliary braking device and has the characteristics of high power density, large braking torque, and compact structure. During traveling, this device can convert the kinetic energy of a vehicle to the heat energy of the cooling liquid and replace the service brake under non-emergency braking conditions. With regard to the constant-speed function of the water medium hydraulic retarder, this study designs a controller based on the neural network proportional–integral–derivative (PID) algorithm to achieve the steady traveling of the vehicle at constant velocity during a downhill course by controlling the filling ratio of the water medium hydraulic retarder. To validate the algorithm’s effectiveness, the dynamic model of the heavy-duty vehicle in the downhill process and the physical model of the water medium hydraulic retarder are developed. Three operating conditions, including a fixed slope, step-changing slope, and continuous changing slope, are set, and a simulation test is carried out in the MATLAB/Simulink environment. The neural network PID algorithm has better adaptability in controlling than the traditional PID algorithm. Thus, it controls the water medium hydraulic retarder such that the braking requirements of heavy-duty vehicles under a changing slope working condition are satisfied, and it performs constant-speed control when the vehicle travels downhill. Therefore, the proposed control method can significantly improve the safety of road traffic.

Full Text
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