基于智能网联汽车行驶状态的自适应优化算法

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中图分类号：U469.72 文献标识码：A 文章编号：1003-8639（2025）10-0004-05

【Abstract】Inorder to improvethe stabilityand safetyof intellgent connected vehicles ontheroad，anadaptive optimizationEKFestimationalgorithmisproposedbasedonthetraditionalEKFalgorithm.Firstly，basedontheanalysis of thedriving state thatisdificult toestimate，theparameters thatneedto beobservedaredeterminedaslongitudinal speed，yaw Angle speedand sidedeflection Angle ofthe centerof mass.Then，basedonthe problem thatthe noise is difcult todealwith inthetraditional EKFalgorithm，theadaptive optimizationalgorithm isusedtoestimateand optimize thesystem noiseand the measurement noise synchronously，sothat the estimation process can beterfit the actual operating conditions.Finally，based on MATLAB and Carsim co-simulation platform，an intelligent connected vehiclemodelisestablished toestimate thedrivingconditions of high adhesionand lowadhesionroad underhigh-speed conditios.Theexperimentalresultsshowthatcomparedwiththecomparisonalgorithm，thealgorithmhasbetereffectin response speed，estimationaccuracyandcurvefiting，and is moresecureforthestabilityandsafetyof thevehicle.

【Key Words】intelligent networked vehicles；driving state;adaptive optimization;EKF

0 引言

在全球倡导低碳与新能源的趋势下，推动新能源绿色出行方式已成为未来发展的方向。（剩余4765字）