基于制动意图识别的增程式重型商用车复合制动控制策略

Composite Braking Control Strategy Based on Braking Intention Recognition for Range-extended Heavy Commercial Vehicles

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 efficiency and braking performance of range-extended heavy commercial vehicle, the fuzzy inference rules of braking intention were designed based on the braking pedal displacement and the rate of brake pedal displacement, which were obtained from a large number of braking data after analysis. A model of braking intention recognition was established by LQV neuro fuzzy system. In consideration of the constraints such as braking force distribution, the motor regenerative braking and the battery, an electromechanical composite braking control strategy was established based on braking intention recognition. And the performance of composite braking control strategy was verified by the simulation of single braking operating condition with 60 km · h-1 initial velocity, simulation of typical Chinese city bus operating cycle （CCBC）, and vehicle tests. The simulation results show that the proposed strategy in this paper can improve braking energy recovery rate as braking force distribution is optimized after driver＇s braking intention being accurately identified, and braking energy recovery rates of light braking and moderate braking are respectively 19.05% and 15.69%in single braking operating condition with 60 km · h-1 initial velocity. In CCBC simulation, the energy recovery rate reaches 16.65%. The proposed strategy can meet the needs of real vehicle, and the battery SOC increases by 0. 019% and 0. 011% respectively in light braking and moderate braking with 30 km · h- 1 initial velocity. Therefore, in terms of braking intention recognition, the electric vehicle＇s energy utilization efficiency can be remarkably improved by the composite braking control strategy, an effective method to promote the economy performance of electric vehicle.