首页> 外文会议>Proceedings of the ASME international design engineering technical conferences and computers and information in engineering conference 2016 >PARAMETER IDENTIFICATION FOR A LONGITUDINAL DYNAMICS MODEL BASED ON ROAD TESTS OF AN ELECTRIC VEHICLE
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PARAMETER IDENTIFICATION FOR A LONGITUDINAL DYNAMICS MODEL BASED ON ROAD TESTS OF AN ELECTRIC VEHICLE

机译:基于电动汽车道路测试的纵向动力学模型的参数辨识

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摘要

This paper presents a method to estimate the parameters of a longitudinal dynamic model using on-road testing of an electric vehicle. Data acquisition was undertaken on our test vehicle, a Toyota Rav4EV 2012, by collating signals from three different sources: Vehicle Measurement System (VMS) (consisting of wheel force, torque, wheel spin, wheel speed and position sensors), Global Positioning System (GPS) and the Controller Area Network (CAN) of the vehicle. A MATLAB/Simulink based nonlinear least square parameter estimation algorithm was used to identify the vehicle parameters including the mass, location of center of gravity, frontal area, coefficient of drag, wheel inertia and road load parameters of the vehicle. A 14 degrees of freedom (DOF), longitudinal dynamics model of the Rav4EV was developed in the MapleSim software using the estimated parameters. The accuracy of the identified parameters and the model was validated by comparing the model output against the experimental data.
机译:本文提出了一种使用电动汽车的道路测试来估算纵向动力学模型参数的方法。数据采集​​是在我们的测试车辆Toyota Rav4EV 2012上进行的,通过整理来自三个不同来源的信号:车辆测量系统(VMS)(由车轮力,扭矩,车轮旋转,车轮速度和位置传感器组成),全球定位系统( GPS)和车辆的控制器局域网(CAN)。使用基于MATLAB / Simulink的非线性最小二乘参数估计算法来识别车辆参数,包括质量,重心位置,额叶面积,阻力系数,车轮惯性和车辆的道路载荷参数。使用估算的参数在MapleSim软件中开发了Rav4EV的14自由度(DOF)纵向动力学模型。通过将模型输出与实验数据进行比较,可以验证所识别参数和模型的准确性。

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