Estimation of tire-road friction coefficient based on combined APF-IEKF and iteration algorithm

Tire-road friction coefficient is an important parameter for vehicle stability and active safety systems. However, precise measurement of tire-road friction coefficient is hard to achieve without expensive equipment. Considering easy availability and good economy, this paper proposes a method which...

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Published in:Mechanical systems and signal processing Vol. 88; pp. 25 - 35
Main Authors: Liu, Y.-H., Li, T., Yang, Y.-Y., Ji, X.-W., Wu, J.
Format: Journal Article
Language:English
Published: Berlin Elsevier Ltd 01.05.2017
Elsevier BV
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ISSN:0888-3270, 1096-1216
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Abstract Tire-road friction coefficient is an important parameter for vehicle stability and active safety systems. However, precise measurement of tire-road friction coefficient is hard to achieve without expensive equipment. Considering easy availability and good economy, this paper proposes a method which first combines auxiliary particle filter and the iterated extended kalman filter (APF-IEKF), and then processes the results of the first step using iteration algorithm. APF-IEKF is used to estimate the slip angle of the front tires with strong nonlinearity and non-Gaussian noise, in which APF filters non-Gaussian noise and reach a preliminary estimation of sideslip angle, then IEKF is used to optimize the result, making the estimation of the sideslip angle more accurate. The iteration algorithm is used to estimate the tire-road friction coefficient based on self-aligning torque, which is more sensitive to tire slip angle and provides faster estimation. In this way, this method can estimate tire road friction coefficient more accurately and in real time. Both numerical simulation in Carsim/Simulink and actual off-vehicle tests in winter are provided to demonstrate the efficiency of the proposed algorithm. •A method that combines APF-IEKF and iteration algorithm is proposed for tire-road friction coefficient.•Tire slip angle estimated by APF-IEKF is much more accurate than common UKF because it is fit for non-Gaussian noise.•Tire-road friction coefficient estimate by proposed method is also much more accurate.
AbstractList Tire-road friction coefficient is an important parameter for vehicle stability and active safety systems. However, precise measurement of tire-road friction coefficient is hard to achieve without expensive equipment. Considering easy availability and good economy, this paper proposes a method which first combines auxiliary particle filter and the iterated extended kalman filter (APF-IEKF), and then processes the results of the first step using iteration algorithm. APF-IEKF is used to estimate the slip angle of the front tires with strong nonlinearity and non-Gaussian noise, in which APF filters non-Gaussian noise and reach a preliminary estimation of sideslip angle, then IEKF is used to optimize the result, making the estimation of the sideslip angle more accurate. The iteration algorithm is used to estimate the tire-road friction coefficient based on self-aligning torque, which is more sensitive to tire slip angle and provides faster estimation. In this way, this method can estimate tire road friction coefficient more accurately and in real time. Both numerical simulation in Carsim/Simulink and actual off-vehicle tests in winter are provided to demonstrate the efficiency of the proposed algorithm. •A method that combines APF-IEKF and iteration algorithm is proposed for tire-road friction coefficient.•Tire slip angle estimated by APF-IEKF is much more accurate than common UKF because it is fit for non-Gaussian noise.•Tire-road friction coefficient estimate by proposed method is also much more accurate.
Tire-road friction coefficient is an important parameter for vehicle stability and active safety systems. However, precise measurement of tire-road friction coefficient is hard to achieve without expensive equipment. Considering easy availability and good economy, this paper proposes a method which first combines auxiliary particle filter and the iterated extended kalman filter (APF-IEKF), and then processes the results of the first step using iteration algorithm. APF-IEKF is used to estimate the slip angle of the front tires with strong nonlinearity and non-Gaussian noise, in which APF filters non-Gaussian noise and reach a preliminary estimation of sideslip angle, then IEKF is used to optimize the result, making the estimation of the sideslip angle more accurate. The iteration algorithm is used to estimate the tire-road friction coefficient based on self-aligning torque, which is more sensitive to tire slip angle and provides faster estimation. In this way, this method can estimate tire road friction coefficient more accurately and in real time. Both numerical simulation in Carsim/Simulink and actual off-vehicle tests in winter are provided to demonstrate the efficiency of the proposed algorithm.
Author Liu, Y.-H.
Wu, J.
Ji, X.-W.
Li, T.
Yang, Y.-Y.
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Keywords Iteration algorithm
Tire-road friction coefficient
APF-IEKF
Self-aligning torque
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Snippet Tire-road friction coefficient is an important parameter for vehicle stability and active safety systems. However, precise measurement of tire-road friction...
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SubjectTerms Algorithms
APF-IEKF
Automotive parts
Computer simulation
Extended Kalman filter
Filters
Friction
Iteration algorithm
Iterative algorithms
Iterative methods
Kalman filters
Noise
Self-aligning torque
Sideslip
Simulation
Slip
Tire-road friction coefficient
Tires
Vehicles
Title Estimation of tire-road friction coefficient based on combined APF-IEKF and iteration algorithm
URI https://dx.doi.org/10.1016/j.ymssp.2016.07.024
https://www.proquest.com/docview/1942191498
Volume 88
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