Real-time estimation of tire–road friction coefficient based on lateral vehicle dynamics

Hu, Juqi; Rakheja, Subhash; Zhang, Youmin

doi:10.1177/0954407020929233

Cited by 41 publications

(25 citation statements)

References 38 publications

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“…As a continuation of the authors’ previous work on TRFC estimation considering lateral vehicle dynamics (lane change maneuvers), 35 this study drives attention to reliable TRFC estimation based on longitudinal vehicle dynamics while in the meanwhile causing relatively small changes in the vehicle speed. The study focuses on the vehicle’s longitudinal maneuvers, which is preferable since a disturbance along the longitudinal axis would be more practical for implementation as opposed to the lateral excitation in real driving conditions.…”

Section: Introductionmentioning

confidence: 82%

Tire–road friction coefficient estimation based on designed braking pressure pulse

Rakheja

Zhang

2021

Proceedings of the Institution of Mechanical Engineers, Part D:

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Knowledge of tire–road friction coefficient (TRFC) is valuable for autonomous vehicle control and design of active safety systems. This paper investigates TRFC estimation on the basis of longitudinal vehicle dynamics. A two-stage TRFC estimation scheme is proposed that limits the disturbances to the vehicle motion. A sequence of braking pressure pulses is designed in the first stage to identify desired minimal pulse pressure for reliable estimation of TRFC with minimal interference with the vehicle motion. This stage also provides a qualitative estimate of TRFC. In the second stage, tire normal force and slip ratio are directly calculated from the measured signals, a modified force observer based on the wheel rotational dynamics is developed for estimating the tire braking force. A constrained unscented Kalman filter (CUKF) algorithm is subsequently proposed to identify the TRFC for achieving rapid convergence and enhanced estimation accuracy. The effectiveness of the proposed methodology is evaluated through CarSim™-MATLAB/Simulink™ co-simulations considering vehicle motions on high-, medium-, and low-friction roads at different speeds. The results suggest that the proposed two-stage methodology can yield an accurate estimation of the road friction with a relatively lower effect on the vehicle speed.

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Section: Introductionmentioning

confidence: 82%

Tire–road friction coefficient estimation based on designed braking pressure pulse

Rakheja

Zhang

2021

Proceedings of the Institution of Mechanical Engineers, Part D:

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“…The concept of smart tires, with use of MEMS, was taken into consideration in [ 57 , 58 , 59 ]. The authors of [ 60 ] analyzed a real-time estimation of tire/road friction coefficients based on sensor measurement on the basis of the vehicle’s lateral dynamics.…”

Section: Literature Reviewmentioning

confidence: 99%

Application of MEMS Sensors for Evaluation of the Dynamics for Cargo Securing on Road Vehicles

Gnap

Jagelčák

Marienka

et al. 2021

Sensors

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Safety is one of the key aspects of the successful transport of cargo. In the case of road transport, the dynamics of a vehicle during normal events such as braking, steering, and evasive maneuver are variable in different places in the vehicle. Several manufacturers provide different dataloggers with acceleration sensors, but the results are not comparable due to different sensor parameters, measurement ranges, sampling frequencies, data filtration, and evaluation of different periods of acceleration. The position of the sensor in the loading area is also important. The accelerations are not the same at all points in the vehicle. The article deals with the measurement of these dynamic events with MEMS sensors on selected points of a vehicle loaded with cargo and with changes in dynamics after certain events that could occur during regular road transport of cargo to analyze the possibilities for monitoring accelerations and the related forces acting on the cargo during transport. The article uses evaluation times of 80, 300, and 1000 ms for accelerations. With the measured values, it is possible to determine the places with a higher risk of cargo damage and not only to adjust the packaging and securing of the cargo, but also to modify the transport routes. Concerning the purposes of securing the cargo in relation to EN 12195-1 and the minimum values of forces for securing the cargo, we focused primarily on the places where the acceleration of 0.5 g was exceeded when analyzing the monitored route. There were 32 of these points in total, all of which were measured by a sensor located at the rear of the semi-trailer. In 31 cases, the limit of 0.5 g was exceeded for an 80-ms evaluation time, and in one case, the value of 0.51 g was reached in the transverse direction for a 300-ms evaluation time.

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“…In this study, the crankshaft coordinate axes are considered to correspond to the vehicle coordinate axes, in which case the product of the crankshaft inertia multiplications in the vehicle coordinates is also equal to zero. Thus: By placing equations ( 32) and (33) in equation ( 31), the gyroscopic moment vector in the vehicle coordinate system is obtained as equation ( 34): In equation ( 34), v is the angular velocity of the engine and I ae is the crankshaft inertia moment around its rotation axis. The direction of the crankshaft rotation can change the direction of the engine rotation in the direction of the wheels rotation or in the opposite direction of their rotation and causes some changes in the gyroscopic torque vector of the engine in the coordinates of the vehicle.…”

Section: Equations Of Engine Rotatingmentioning

confidence: 99%

“…For this reason, a lot of researches have been done in the form of experimental and the preparation of suitable mathematical models for the tire. [29][30][31][32][33][34] One of the complete tire models is Pacejka model, which examines the longitudinal and lateral forces of the tire under different inputs such as camber angle and vertical force of the wheels. [35][36][37][38][39] In vehicles, the engine is usually installed in two positions: in-line engine (crankshaft along the length of the vehicle) and transverse engine (crankshaft along the width of the vehicle).…”

Section: Introductionmentioning

confidence: 99%

The influence of engine gyroscopic moments on vehicle transient handling

Shahabi

Kazemian

Farahat

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part D:

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This study presents the dynamics of a 15-DOF model of the vehicle by performing simulations to investigate the vehicle handling dynamics in J-turn maneuver. Using Newton’s equations of motion, the equations of motion for the sprung and unsprung masses are all written in the vehicle coordinate system and the tire is modeled with the Pacejka 89 model. Since the engine crankshaft has a rotation relative to the vehicle coordinate system, in order to investigate the effect of the engine gyroscopic moments on the vehicle handling dynamics, the effect of the crankshaft rotation on the torque vector of external forces is considered. The direction of crankshaft rotation can change the direction of engine rotation in the direction of the wheels rotation or in the opposite direction of their rotation, which causes some changes in the gyroscopic torque vector of the engine. Due to the rotation speed of the crankshaft and its moment of inertia, the gyroscopic moments which resulted from the angular momentum of the engine crankshaft are considerable. These gyroscopic moments are added to the torque equation of external forces in the vehicle coordinate system and affect the vehicle handling dynamics. By using the numerical method of Newmark, vehicle’s dynamic behavior is investigated and the validation of its dynamic behavior is done by ADAMS/Car software. This study shows that in transverse engine, if the direction of engine rotation is in the opposite direction of the wheels, the vehicle handling dynamics is improved.

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Real-time estimation of tire–road friction coefficient based on lateral vehicle dynamics

Cited by 41 publications

References 38 publications

Tire–road friction coefficient estimation based on designed braking pressure pulse

Tire–road friction coefficient estimation based on designed braking pressure pulse

Application of MEMS Sensors for Evaluation of the Dynamics for Cargo Securing on Road Vehicles

The influence of engine gyroscopic moments on vehicle transient handling

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