In view of the problem that the hybrid electric vehicle ( HEV) adopting the control strategy com-monly developed with specific driving cycle may not necessarily achieve optimal performance in real operation condi-tion, the issue of energy management strategy for HEV in real road condition is converted into the issue of stochastic linear optimal control. The quadratic state-space equation for HEV is set up with consideration of the thermal state of three-way catalytic converter ( TWC) , and with minimizing the fuel consumption of engine and the emissions at the exit of TWC as optimization objectives, a Kalman filtering estimation is conducted on the real states including battery SOC, vehicle speed, TWC temperature and the emissions at TWC exit, so as to do the optimal feedback for output variables such as motor power and engine power. The simulation results show that compare with rule control, the linear quadratic Gaussian ( LQG) optimal control strategy set up can shorten the light-off time of TWC by around 160s and increase the converting rate of HC and CO obviously, while meeting the power performance requirements of vehicle.%鉴于采用通常在特定工况下开发的控制策略的混合动力汽车在实际路况下的性能未必能达到最优的问题,将实际道路下的混合动力汽车能量管理策略问题转化为标准路况下的随机线性最优控制问题。建立了包含三效催化转化器热状态的混合动力汽车二次型状态空间方程,以发动机燃油消耗和三效催化转化器出口处的排放最小为优化目标,对蓄电池SOC、车速、三效催化转化器温度和出口排放等实际状态进行卡尔曼滤波估计,以对电机功率和发动机功率等输出变量进行最优反馈。仿真结果表明,与规则控制相比,所建立的随机最优控制策略能在满足车辆动力性要求的前提下,三效催化转化器的起燃时间约缩短160s,HC和CO的转化率明显提高。
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