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首页> 外文期刊>SAE International Journal of Vehicle Dynamics, Stability, and NVH >Longitudinal Vehicle Dynamics Modeling and Parameter Estimation for Plug-in Hybrid Electric Vehicle
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Longitudinal Vehicle Dynamics Modeling and Parameter Estimation for Plug-in Hybrid Electric Vehicle

机译：车辆纵向动力学建模和插件混合动力参数估计车辆

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摘要

System identification is an important aspect in model-based control design which is proven to be a cost-effective and time saving approach to improve the performance of hybrid electric vehicles (HEVs). This study focuses on modeling and parameter estimation of the longitudinal vehicle dynamics for Toyota Prius Plug-in Hybrid (PHEV) with power-split architecture. This model is needed to develop and evaluate various controllers, such as energy management system, adaptive cruise control, traction and driveline oscillation control. Particular emphasis is given to the driveline oscillations caused due to low damping present in PHEVs by incorporating flexibility in the half shaft and time lag in the tire model. Accurate and reliable vehicle dynamics parameters that control the vehicle motion are estimated by acquiring experimental data from longitudinal maneuvers of the PHEV equipped with a vehicle measurement system (VMS), global positioning system (GPS) and inertial measurement unit (IMU). The simulated model with estimated parameters is analyzed for longitudinal dynamics by comparing with experimental data from on-road testing.
机译：系统识别是一个重要的方面被证明是基于模型的控制设计一个具有成本效益和节省时间的方法提高混合动力的性能车辆(戊肝病毒)。和纵向的参数估计丰田普锐斯混合动力汽车动力(PHEV)功率分流体系结构。需要开发和评估各种控制器,如能源管理系统,自适应巡航控制、牵引和动力传动系统振动控制。由于低引起的动力传动系统振荡将阻尼在插电式混合动力车灵活的半轴和时间滞后轮胎模型。控制车辆的动力学参数运动估计是获取实验数据从纵向PHEV的演习配备车辆测量系统(VMS),全球定位系统(GPS)和惯性测量单元(IMU)。估计参数是纵向的分析动力学与实验数据进行比较行车测试。

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