The invention discloses an unmanned driving energy consumption optimization method for a pure electric heavy truck. The method comprises the steps: training an RBF neural network model based on historical data affecting energy consumption of a vehicle, and obtaining an evaluation model; and inputting real-time vehicle operation data into the evaluation model, and determining an optimal output torque in actual vehicle operation, wherein the historical data influencing the vehicle energy consumption at least includes historical road condition information, a first vehicle technical parameter, first vehicle use information and climate information when the first vehicle runs; and the real-time vehicle operation data at least includes real-time road condition information, a second vehicle technical parameter, second vehicle use information and climate information when the second vehicle runs. Technical problems that due to a fact that output power of a conventional unmanned heavy truck is fixed, output adjustment cannot be performed according to actual road conditions, and energy consumption is large are solved.
本发明申请公开了一种纯电动重卡无人驾驶能耗优化方法,包括基于影响车辆能耗的历史数据,训练RBF神经网络模型,得到评估模型;将实时的车辆运行数据输入所述评估模型中,确定实际车辆运行中的最优输出扭矩;其中,所述影响车辆能耗的历史数据至少包括历史路况信息、第一车辆技术参数、第一车辆使用信息和第一车辆行驶时的气候信息;所述实时的车辆运行数据,至少包括实时路况信息、第二车辆技术参数、第二车辆使用信息和第二车辆行驶时的气候信息。本发明申请解决了由于常规的无人驾驶重卡的输出功率固定,导致不能根据实际道路情况进行输出调整、能源消耗大的技术问题。
Unmanned driving energy consumption optimization method for pure electric heavy truck
一种纯电动重卡无人驾驶能耗优化方法
2020-10-23
Patent
Elektronische Ressource
Chinesisch
IPC: | B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion |
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