Enhanced maximum tire-road friction coefficient estimation based advanced emergency braking algorithm

Taewoo Kim, Jaewan Lee, K. Yi
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引用次数: 12

Abstract

This paper presents the maximum tire-road friction coefficient estimation algorithm which considers about the effect of states. Tire force information is an important factor for active safety system. However, it is difficult to estimate due to the dependency on many states such as vehicle speed, tire pressure, and tire wear. In this paper, several experimental researches about the effect of states on the maximum friction coefficient and previous maximum tire-road friction coefficient estimation algorithms are reviewed and summarized. The influential states and the estimation method which doesn't require extra sensors were determined and combined. The proposed algorithm consists of two parts: an interacting multiple models (IMM) based maximum tire-road friction coefficient estimation and an updating sequence based on the effect of vehicle speed. To validate the algorithm, the closed-loop simulation with the advanced emergency braking system (AEBS) has been conducted. It has been shown that the proposed estimation algorithm could enhance the performance of AEBS algorithm.
基于改进的高级紧急制动算法的最大轮胎路面摩擦系数估计
提出了考虑状态影响的轮胎-路面最大摩擦系数估计算法。胎力信息是主动安全系统的重要因素。然而,由于依赖于许多状态,如车速、胎压和轮胎磨损,很难估计。本文对状态对最大摩擦系数影响的实验研究以及以往最大轮胎-路面摩擦系数估计算法进行了综述和总结。确定并结合影响状态和不需要额外传感器的估计方法。该算法由两部分组成:基于交互多模型(IMM)的最大轮胎-路面摩擦系数估计和基于车速影响的更新序列。为了验证该算法的有效性,对先进紧急制动系统(AEBS)进行了闭环仿真。实验结果表明,所提出的估计算法可以提高AEBS算法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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