PID plus fuzzy logic method for torque control in traction control system

Li, H. Z.; Li, L.; He, Lei; Kang, Mingxin; Song, Jingyan; Yu, Liangyao; Wu, Chong

doi:10.1007/s12239-012-0041-4

Cited by 51 publications

(30 citation statements)

References 14 publications

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“…If the active control system could estimate the friction limitation at the time driver begins to steer and initiatives to reduce the speed, the lateral dynamics of the vehicle would be improved [4]. Wheel braking under the different road condition, we usually can't get the real-time value of road friction coefficient, which leads the instability of the whole control process [7,8]. So road friction coefficient has an important significance in the vehicle chassis electronic control system design.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Road Friction Coefficient in Different Road Conditions Based on Vehicle Braking Dynamics

Zhao

Lin

et al. 2017

Chin. J. Mech. Eng.

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The accurate estimation of road friction coefficient in the active safety control system has become increasingly prominent. Most previous studies on road friction estimation have only used vehicle longitudinal or lateral dynamics and often ignored the load transfer, which tends to cause inaccurate of the actual road friction coefficient. A novel method considering load transfer of front and rear axles is proposed to estimate road friction coefficient based on braking dynamic model of two-wheeled vehicle. Sliding mode control technique is used to build the ideal braking torque controller, which control target is to control the actual wheel slip ratio of front and rear wheels tracking the ideal wheel slip ratio. In order to eliminate the chattering problem of the sliding mode controller, integral switching surface is used to design the sliding mode surface. A second order linear extended state observer is designed to observe road friction coefficient based on wheel speed and braking torque of front and rear wheels. The proposed road friction coefficient estimation schemes are evaluated by simulation in ADAMS/Car. The results show that the estimated values can well agree with the actual values in different road conditions. The observer can estimate road friction coefficient exactly in real-time and resist external disturbance. The proposed research provides a novel method to estimate road friction coefficient with strong robustness and more accurate.

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Section: Introductionmentioning

confidence: 99%

Estimation of Road Friction Coefficient in Different Road Conditions Based on Vehicle Braking Dynamics

Zhao

Lin

et al. 2017

Chin. J. Mech. Eng.

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“…PSR is primarily influenced by the SOC of the vehicle, and TSF is primarily determined by the amount of vehicle slip. Optimal operating points based on vehicle speed and torque demand at the wheels are used as reference to the set points for the control algorithms, similar to the work presented in [13] and [16]. The correlation between the SOC and the torque demand with vehicle speed is used for the EM controller.…”

Section: Supervisory Controller Developmentmentioning

confidence: 99%

“…The traction control is achieved by maintaining the wheel slip at a desired value by controlling the wheel slip at the optimal value, improving safety under difficult weather conditions. In [16], a new torque control method for various drive-slip conditions involving abrupt changes in the road friction. This method is based on a proportional-integral-differential (PID) plus fuzzy logic controller for driving torque regulation, which consists of a PID controller and a fuzzy logic controller.…”

Section: Introductionmentioning

confidence: 99%

Concurrent Design of Energy Management and Vehicle Traction Supervisory Control Algorithms for Parallel Hybrid Electric Vehicles

DOKUYUCU

Çakmakçı

2016

IEEE Trans. Veh. Technol.

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In this paper, concurrent design of energy management (EM) and traction control algorithms for a vehicle equipped with a parallel hybrid powertrain is studied. This paper focuses on designing the two control algorithms together as one control design problem, which are traditionally considered separately. First, optimal control actions and operating points are obtained by applying dynamic programming (DP). Then, this information is used for developing a rule-based supervisory controller. Our objective is to minimize the fuel consumption and the wheel slip simultaneously. Two control problems are also solved separately and compared with the concurrent solution. Results show that promising benefits can be obtained by using the concurrent design approach rather than considering two control problems separately. Under the same conditions, the vehicle with the concurrent supervisory controller is 16% more efficient in fuel consumption and experiences 12% less wheel slip, assuming slippery road friction conditions. Index Terms-Concurrent controllers, hybrid electric vehicles (HEVs). 0018-9545

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“…T B , T FLC , and T PID might be calculated in the basic engine torque controller, which is discussed in detail in [10]. T B is the torque base, which is calculated by the engine output torque from EMS, when the slip speeds of driving wheels exceed the threshold of the target slip speed.…”

Section: Structure Of the Correctional Tcs Controllermentioning

confidence: 99%

“…A sliding-mode strategy and a proportional-integral-derivative (PID) plus fuzzy logic method were adopted to compensate the friction coefficient variation. [9,10] A new hybrid model and a model predictive control strategy were utilised by Borrelli et al to decrease the control error. [11] A fuzzy logic controller was presented in [12,13] to deal with the system nonlinearity.…”

Section: Introductionmentioning

confidence: 99%

A novel fuzzy logic correctional algorithm for traction control systems on uneven low-friction road conditions

Zhang

et al. 2015

Vehicle System Dynamics

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The traction control system (TCS) might prevent excessive skid of the driving wheels so as to enhance the driving performance and direction stability of the vehicle. But if driven on an uneven low-friction road, the vehicle body often vibrates severely due to the drastic fluctuations of driving wheels, and then the vehicle comfort might be reduced greatly. The vibrations could be hardly removed with traditional drive-slip control logic of the TCS. In this paper, a novel fuzzy logic controller has been brought forward, in which the vibration signals of the driving wheels are adopted as new controlled variables, and then the engine torque and the active brake pressure might be coordinately re-adjusted besides the basic logic of a traditional TCS. In the proposed controller, an adjustable engine torque and pressure compensation loop are adopted to constrain the drastic vehicle vibration. Thus, the wheel driving slips and the vibration degrees might be adjusted synchronously and effectively. The simulation results and the real vehicle tests validated that the proposed algorithm is effective and adaptable for a complicated uneven low-friction road.

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PID plus fuzzy logic method for torque control in traction control system

Cited by 51 publications

References 14 publications

Estimation of Road Friction Coefficient in Different Road Conditions Based on Vehicle Braking Dynamics

Estimation of Road Friction Coefficient in Different Road Conditions Based on Vehicle Braking Dynamics

Concurrent Design of Energy Management and Vehicle Traction Supervisory Control Algorithms for Parallel Hybrid Electric Vehicles

A novel fuzzy logic correctional algorithm for traction control systems on uneven low-friction road conditions

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