基于多传感数据融合滤波的纵向坡度识别算法

doi:10.3901/JME.2018.14.116

机械工程学报 ›› 2018, Vol. 54 ›› Issue (14): 116-124.doi: 10.3901/JME.2018.14.116

基于多传感数据融合滤波的纵向坡度识别算法

雍文亮, 管欣, 王博, 卢萍萍

吉林大学汽车仿真与控制国家重点试验室长春 130022

收稿日期:2017-10-31 修回日期:2018-04-09 出版日期:2018-07-20 发布日期:2018-07-20
通讯作者: 卢萍萍(通信作者),女,1982年出生,博士,讲师。主要研究方向为汽车动态仿真与控制。E-mail:lupingping@jlu.edu.cn
作者简介:雍文亮,男,1988年出生,博士研究生。主要研究方向为汽车动态仿真与控制。管欣,男,1961年出生,教授,博士研究生导师。主要研究方向为汽车动态仿真与控制;王博,男,1987年出生,博士研究生。主要研究方向为汽车动态仿真与控制。
基金资助:
长城开发型汽车驾驶模拟器开发资助项目（3H006I122462）。

Identification Algorithm of Longitudinal Road Slope Based on Multi-sensor Data Fusion Filtering

YONG Wenliang, GUAN Hsin, WANG Bo, LU Pingping

State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022

Received:2017-10-31 Revised:2018-04-09 Online:2018-07-20 Published:2018-07-20

摘要/Abstract

摘要： 道路纵向坡度是汽车动力传动电控系统和底盘主动安全电控系统控制策略的关键参量。以往对道路坡度估算的研究大多假定坡度为常值，且采用单一传感信息估算纵向坡度。然而实际道路和汽车行驶工况复杂多变，易导致传感信号失真甚至错误，采用单一的坡度道路模型和传感信息很难保证坡度估算值的精度。建立定坡度和定坡度变化率两个道路模型，利用车辆纵向动力学和加速度传感两个量测，采用多传感数据融合滤波算法通过加权融合获得精确的坡度估计值。通过驾驶模拟器场地试验，验证了该方法能实时有效地对复杂道路坡度进行估计，辨识精度较高，为汽车先进电控系统控制策略提供基础。

关键词: Kalman滤波, 多传感数据融合, 驾驶模拟器, 坡度识别

Abstract: The longitudinal road slope is the key parameter of the control strategy of vehicle power transmission electronic control system and the chassis active safety electric control system. Most previous researches on road slope identification mainly assume that the road slope is constant, and the longitudinal road slope is estimated by using a single sensor information. However, the complexities of road and driving conditions can easily lead to distortion or even error of the sensors information. It is difficult to ensure the identification accuracy of road slope by using a single road slope model and sensor information. Two road slope models including the fixed road slope model and fixed road slope rate model are established, and a real-time identification approach of longitudinal road slope based on multi-sensor data fusion filtering algorithm is applied to estimate the road slope through the weighted fusion of two measurements including the vehicle longitudinal dynamics and acceleration sensor information. The field test based on the driving simulator is carried out. The results show that the proposed algorithm can effectively estimate the complex road slope in real time with high identification accuracy, which can be applied to many kinds of real-time vehicle electric control systems.

Key words: driving simulator, Kalman filtering, multi-sensor data fusion, road slope identification

中图分类号:

U461

雍文亮, 管欣, 王博, 卢萍萍. 基于多传感数据融合滤波的纵向坡度识别算法[J]. 机械工程学报, 2018, 54(14): 116-124.

YONG Wenliang, GUAN Hsin, WANG Bo, LU Pingping. Identification Algorithm of Longitudinal Road Slope Based on Multi-sensor Data Fusion Filtering[J]. Journal of Mechanical Engineering, 2018, 54(14): 116-124.

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基于多传感数据融合滤波的纵向坡度识别算法

Identification Algorithm of Longitudinal Road Slope Based on Multi-sensor Data Fusion Filtering

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