Adaptive state observers for driving dynamics – online estimation of tire parameters under real conditions

Bechtloff, Jakob; Ackermann, Carlo; Isermann, Rolf

doi:10.1007/978-3-658-09711-0_46

Cited by 6 publications

(2 citation statements)

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“…More recently, in Bechtloff et al (2015, 2016), an online CS observer for low-frequency maneuvers on public roads is presented. The estimation method presented shows good estimation results even under less extreme maneuvers on public roads.…”

Section: Introductionmentioning

confidence: 99%

Virtual sensor for real-time estimation of the vehicle sideslip angle

Singh

2019

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Purpose The vehicle sideslip angle is an important state of vehicle lateral dynamics and its knowledge is crucial for the successful implementation of advanced driver-assistance systems. Measuring the vehicle sideslip angle on a production vehicle is challenging because of the exorbitant price of a physical sensor. This paper aims to present a novel framework for virtually sensing/estimating the vehicle sideslip angle. The desired level of accuracy for the estimator is to be within +/− 0.2 degree of the actual sideslip angle of the vehicle. This will make the precision of the proposed estimator at par with expensive commercially available sensors used for physically measuring the vehicle sideslip angle. Design/methodology/approach The proposed estimator uses an adaptive tire model in conjunction with a model-based observer. The performance of the estimator is evaluated through experimental tests on a rear-wheel drive vehicle. Findings Detailed experimental results show that the developed system can reliably estimate the vehicle sideslip angle during both steady state and transient maneuvers, within the desired accuracy levels. Originality/value This paper presents a novel framework for vehicle sideslip angle estimation. The presented framework combines an adaptive tire model, an unscented Kalman filter-based axle force observer and data from tire mounted sensors. Tire model adaptation is achieved by making extensions to the magic formula, by accounting for variations in the tire inflation pressure, load, tread-depth and temperature. Predictions with the adapted tire model were validated by running experiments on the Flat-Trac® machine. The benefits of using an adaptive tire model for sideslip angle estimation are demonstrated through experimental tests. The performance of the observer is satisfactory, in both transient and steady state maneuvers. Future work will focus on measuring tire slip angle and road friction information using tire mounted sensors and using that information to further enhance the robustness of the vehicle sideslip angle observer.

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Section: Introductionmentioning

confidence: 99%

Virtual sensor for real-time estimation of the vehicle sideslip angle

Singh

2019

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“…More recently, in [9,10], an online cornering stiffness observer for low frequency maneuvers on public roads is presented. The estimation method presented shows good estimation results even under less extreme maneuvers on public roads.…”

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confidence: 99%

Vehicle Sideslip Angle Estimation Based on Tire Model Adaptation

Singh

2019

Electronics

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Information about the vehicle sideslip angle is crucial for the successful implementation of advanced stability control systems. In production vehicles, sideslip angle is difficult to measure within the desired accuracy level because of high costs and other associated impracticalities. This paper presents a novel framework for estimation of the vehicle sideslip angle. The proposed algorithm utilizes an adaptive tire model in conjunction with a model-based observer. The proposed adaptive tire model is capable of coping with changes to the tire operating conditions. More specifically, extensions have been made to Pacejka's Magic Formula expressions for the tire cornering stiffness and peak grip level. These model extensions account for variations in the tire inflation pressure, load, tread depth and temperature. The vehicle sideslip estimation algorithm is evaluated through experimental tests done on a rear wheel drive (RWD) vehicle. Detailed experimental results show that the developed system can reliably estimate the vehicle sideslip angle during both steady state and transient maneuvers.

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State Estimation of Vehicles

Isermann

2021

Automotive Control

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Adaptive state observers for driving dynamics – online estimation of tire parameters under real conditions

Cited by 6 publications

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Virtual sensor for real-time estimation of the vehicle sideslip angle

Virtual sensor for real-time estimation of the vehicle sideslip angle

Vehicle Sideslip Angle Estimation Based on Tire Model Adaptation

State Estimation of Vehicles

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