Optimal Energy Management Strategy for Extended-range Electric Vehicle via GA-BP Driving Pattern Recognition
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摘要: 为了改善增程式电动汽车在复杂工况下的燃油经济性，提出一种利用遗传算法优化的反向传播神经网络(GA-BP)工况识别的规则能量管理策略。针对BP算法收敛速度慢、泛化能力差的问题，采用遗传算法优化BP神经网络。以中国工况中市区、市郊、高速作为工况类别，工况速度曲线为BP神经网络训练样本，构建遗传算法优化的BP神经网络识别器。在识别的工况下，以能耗费用为燃油经济性的评价指标，采用果蝇算法优化规则能量管理策略参数。仿真结果表明，使用遗传算法优化的BP神经网络识别正确率达到99.99%，优于未进行优化的神经网络识别；基于工况识别的能量管理策略，合理分配增程式电动汽车工作模式，有效的降低燃油消耗。Abstract: In order to improve the fuel economy of extended-range electric vehicle(E-REV) under complex driving condition, a rule energy management strategy based on BP neural network optimized by genetic algorithm is proposed. The genetic algorithm is used to optimize BP neural network for overcoming the shortcomings of slow convergence speed and poor generalization ability of BP neural network. City cycle of China include urban, suburban and expressway driving circle are used as the velocity curves of the three driving circles for training samples. Then, the rule energy management strategy is optimized under the identified driving pattern. The results show that the accuracy rate of driving pattern recognition of BP neural network optimized by genetic algorithm is 99.99%, which is higher than that without genetic algorithm. And the fuel economy of E-REV is improved under the energy management strategy based on driving pattern recognition, which is reasonable distribution of the working mode of the E-REV.
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表 1 增程式电动汽车参数
参数单位 参数值 整车质量M/kg 6 000 轮胎半径r/m 0.376 0 发动机最高扭矩Tfc-max/(Nm) 250 发动机最高转速ωfc-max/(r·min-1) 6 000 发动机最高功率Pfc-max/kw 157 发电机最高扭矩Tgc-max/(Nm) 250 发电机最高转速ωgc-max/(r·min-1) 4 500 发电机最高功率Pgc-max/kW 117.8 驱动电机最高扭矩Tmc-max/(Nm) 850 驱动电机最高转速ωmc-max/(r·min-1) 4 000 驱动电机最高功率Pmc-max/kW 356 电池容量C/(A·h) 37 电池模块数n 16 主减速比i 6.143 
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表 3 是否应用GA优化BP网络工况识别对比
识别方式 工况类型 最大误差 均方差 识别率 GA-BP 市区工况 0.0768 0.0173 100% 市郊工况 0.0185 0.0139 99.98% 高速公路工况 0.00000394 0.000295 100% 综合 0.0768 0.0033 99.99% BP 市区工况 0.6952 0.1615 60% 市郊工况 0.0615 0.0988 99.95% 高速公路工况 0.2272 0.0465 99.94% 综合 0.6952 0.1168 89.37
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表 4 规则能量管理策略
驱动模式 工作状态 电池驱动纯电动模式 SOC>SOChigh、Pr < Pc-max 电池放电单独驱动 电池和增程器双动力混合驱动模式 SOClow≤SOC≤SOChigh、Plast≤Pr 发动机在发动机输出功率等于上一时刻输出功率 SOC>SOChigh、Pr≥Pc-max、P≤Pr 发动机处于最佳功率工点 增程器单独驱动且电池充电模式 SOC < SOClow 电池电量过低, 增程器输出的功率为充电功率与驱动需求功率之和 SOClow≤SOC≤SOChigh、Plast>Pr 发动机输出功率与上一秒时刻输出功率相等, 充电的功率为Plast-Pr SOC>SOChigh、Pr≥Pc-max、P>Pr 充电的功率为P-Pr
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表 6 3种方式能耗费用
元 类型 油耗 电耗 总费用 未使用 23.24 -1.71 21.54 BP 24.39 -2.45 21.94 GA-BP 15.75 2.05 17.80
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