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为了提高增程式重型商用车制动能量回收率和制动性能,通过分析大量实车制动数据,以制动踏板位移和制动踏板位移变化率为输入设计制动意图的模糊推理规则,采用LQV神经模糊系统建立制动意图识别模型;在制动力分配要求、电机再生制动约束、蓄电池约束等约束条件下,基于制动意图识别建立机-电复合制动控制策略,并通过60km·h~(-1)初速单次制动工况仿真、中国典型城市公交工况(CCBC工况)仿真和实车试验验证复合制动控制策略的性能。研究结果表明:提出的复合制动控制策略能够准确识别驾驶人的制动意图,优化制动力分配,提高制动能量回收率;其中60km·h~(-1)初速单次制动工况下轻度制动和中度制动的能量回收率分别为19.05%和15.69%,CCBC工况下制动能量回收率达到了16.65%;提出的复合制动控制策略能够满足实车制动需求,在30km·h~(-1)初速单次制动工况下轻度制动和中度制动时,蓄电池SOC分别上升了0.019%和0.011%。因此,基于制动意图识别的复合制动控制策略能够显著提高电动汽车的能量利用效率,是一种提升电动汽车经济性的有效方法。
In order to improve the braking energy recovery and braking performance of extended-range heavy commercial vehicles, by analyzing a large number of actual vehicle braking data, the fuzzy inference rules of braking intention are designed based on brake pedal displacement and brake pedal displacement. LQV neuro-fuzzy system is established to identify the braking intension. Under the constraints of braking force distribution requirements, motor regenerative braking constraints and battery constraints, a machine-electric hybrid braking control strategy is established based on braking intent recognition, and through 60km · h ~ (-1) initial speed single-brake condition simulation, the simulation of China’s typical urban bus operating condition (CCBC) and actual vehicle test to verify the performance of composite brake control strategy. The results show that the proposed composite braking control strategy can accurately identify the driver’s intention of braking, optimize the braking force distribution, and improve the recovery rate of braking energy. Among them, under 60km · h ~ (-1) initial speed single-braking condition The energy recovery rates of mild braking and moderate braking are 19.05% and 15.69% respectively, and the recovery rate of braking energy under CCBC is 16.65%. The proposed hybrid braking control strategy can meet the demand of actual vehicle braking, The battery SOC increased by 0.019% and 0.011% respectively under mild braking and moderate braking under the single-speed braking condition of 30km · h ~ (-1). Therefore, the composite braking control strategy based on braking intent identification can significantly improve the energy efficiency of electric vehicles, which is an effective way to improve the economy of electric vehicles.