{"title":"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","authors":"Taewoo Kim, Jaewan Lee, K. Yi","doi":"10.1109/IVS.2015.7225796","DOIUrl":null,"url":null,"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.","PeriodicalId":294701,"journal":{"name":"2015 IEEE Intelligent Vehicles Symposium (IV)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Enhanced maximum tire-road friction coefficient estimation based advanced emergency braking algorithm\",\"authors\":\"Taewoo Kim, Jaewan Lee, K. Yi\",\"doi\":\"10.1109/IVS.2015.7225796\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":294701,\"journal\":{\"name\":\"2015 IEEE Intelligent Vehicles Symposium (IV)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-08-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE Intelligent Vehicles Symposium (IV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IVS.2015.7225796\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Intelligent Vehicles Symposium (IV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IVS.2015.7225796","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Enhanced maximum tire-road friction coefficient estimation based advanced emergency braking algorithm
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.