摘要
以轮毂液压混合动力重型商用车作为研究对象,建立了3自由度侧翻参考模型。在此基础上设计了一种有效的汽车防侧翻预警系统装置,并完成了侧翻指标观测器以及相应控制策略的构建。据此确定侧翻预警算法的指标,采用遗传算法优化BP神经网络(GANN)后将其引入到传统的TTR预警算法中,从而得到基于GANN-TTR的侧翻预警算法,仿真测试结果表明这个侧翻预警算法显著提高了预警精度,同理想预警曲线基本吻合。
This article considers the wheel hydraulic hybrid heavy-duty commercial vehicle.First,a 3 DOF rollover reference model is completed.A rollover indicator observer is established,and based on the model,a rollover warning algorithm is completed.The BP neural network is optimized using a genetic algorithm(GA),and then the GANN is introduced into the traditional TTR warning algorithm to complete a new rollover.The establishment of an early warning algorithm is completed based on GANN-TTR.Simulation test results show that the rollover early warning algorithm proposed in this paper significantly improves the early warning accuracy.The curve obtained by the algorithm is basically consistent with the ideal early warning curve.
作者
曲彩悦
QU Caiyue(Department of Traffic Engineering, Yantai Automobile Engineering Professional College, Yantai 265500, China)
出处
《微型电脑应用》
2020年第9期101-103,共3页
Microcomputer Applications
关键词
车辆侧翻预警系统
BP神经网络
算法设计
实现路径
vehicle rollover early warning system
BP neural network
algorithm design
implementation path
