| The Electro-Mechanical Transmission (EMT) system can meet the specialrequirements of the heavy-duty and off-road vehicles for the wide speed range and drivingpower, the electric power demand of auxiliary system and specific function system andother requirements that are different from general light vehicles. The main functions ofEMT control strategy are the judgment and switching of EMT system working mode, thecalculation and distribution of driving power demand, parts working state control andsystem dynamic process control, etc. Compared with other forms of hybrid drive system,the power distribution and coordination in EMT system is more complex, so the study ofcontrol strategy put forward higher requirements. The energy management and controlstrategy is the key point for EMT system keeping normal and efficient operation. In thispaper, the optimal control strategy is carried out for a heavy-duty vehicle equipped withEMT system.First of all, the EMT system is analyzed in features, and the forward simulation modelis built for the development of the system control strategy on the basis of Matlab/Simulinkplatform. As a evaluation benchmark for the optimal control strategy, the rules basedcomposite control strategy is developed, including the division of system work patterns andthe switching rules, the distribution rules of system power requirements, thedecision-making method of power components control, etc. After that, the effect of thecomposite control strategy is examined under the heavy-duty vehicle driving cycle.On the basis of power flow characteristics analysis, the optimal control model of EMTsystem is built considering the system dynamic performance and the of fuel economy at thesame time. Then, the minimum principle is used to solve the optimal control problem. Andthen, in order to satisfy the adaptability of different operating conditions and driving habits,a fuzzy PID controller is applied to adjust the co-state value. The performance of theoptimal control strategy is improved. Considering the characteristics of system dynamicresponse, LQR method is applied to track the optimal control target.In order to further improve the performance of EMT system, the on-line prediction ofthe system future torque demand is researched. The torque requirement information of EMT system can be regarded as stochastic time series. Based on the current and past datacollecting from the EMT system, the Auto Regressive model (AR) and Auto Regressivemodel with external input (ARX) are chosen for the on-line prediction. The step by stepprediction algorithm, fixed gain prediction algorithm and adaptive recursive predictionalgorithm are respectively applied to accomplish the real-time forecasting of system torquedemand. Through the forecast information to control the torque of engine, the batteryoverload phenomenon is effectively improved.Based on the system torque demand, model predictive control (MPC) is applied torealize the optimal allocation of system mechanical and electrical power flows. In order tomeet the demand for real-time optimal control, the improved prime-dual method is used toquickly solve the QP problem in predictive control. After that, the simulation is carried outfor MPC control strategy and the real-time performance and control effect of the algorithmare verified.The hardware in the loop simulation experiment is presented based on dSPACEplatform. The experiment results show that the optimal control strategy can effectivelyensure the normal operation of the EMT system. In order to verify the performance of EMTsystem, the vehicle road test is carried out. The results show that the power performanceand fuel economy of EMT system both meet the design requirements. |
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