李克強(qiáng)++羅禹貢++邊明遠(yuǎn)++戴一凡++陳龍

摘 要：汽車狀態(tài)參數(shù)的準(zhǔn)確獲得是保證汽車主動(dòng)安全系統(tǒng)有效性的重要要求。分布式電驅(qū)動(dòng)車輛的新型結(jié)構(gòu)為傳統(tǒng)基于動(dòng)力學(xué)的狀態(tài)參數(shù)估計(jì)方法的突破提供了可能。通過分析基于運(yùn)動(dòng)學(xué)與動(dòng)力學(xué)方法各自不同的誤差特性，該文提出了對(duì)兩種估計(jì)方法的估計(jì)結(jié)果進(jìn)行融合處理的分布式電驅(qū)動(dòng)車輛狀態(tài)參數(shù)估計(jì)方法。利用理論推導(dǎo)，證明了該方法將能夠有效的提高不同工況下的估計(jì)精度，提高估計(jì)方法的工況適應(yīng)性。為驗(yàn)證該方法的有效性，開發(fā)了CarSim與Simulink聯(lián)合仿真試驗(yàn)平臺(tái)。仿真結(jié)果表明，所提出的誤差加權(quán)的融合狀態(tài)觀測(cè)方法提高了分布式電驅(qū)動(dòng)車輛狀態(tài)參數(shù)觀測(cè)精度和魯棒性。

關(guān)鍵詞：分布式電驅(qū)動(dòng)車輛 車輛狀態(tài)估計(jì) 多方法融合

Vehicle State Estimation Based on Kinematic Model and Dynamic Model Merging

Li Keqiang Luo Yugong Bian Mingyuan Dai Yifan Chen Long

（Tsinghua University）

Abstract：Vehicle state parameters are essential for active safety control. Distributed electric vehicle with a new structure brings a breakthrough for the traditional dynamics state parameter estimation method. This paper presents a novel estimation method for distributed electric drive vehicle by analyzing different characteristics of the estimation errors of kinematics and dynamics estimation methods. This method merges the results of the two estimation methods with weighting coefficients. With a mathematical deduction， it shows that this method can effectively improve the estimation accuracy and applicability under different conditions. A CarSim and Simulink co-simulation test platform is developed to verify the effectiveness of the method. Simulation results show that the proposed method improves the state estimation accuracy and robustness of distributed electric drive vehicle state parameters.

Key Words：Distributed electric vehicle； Vehicle state estimation； Multi-method merging