Robust gain-scheduled output feedback yaw stability control for in-wheel-motor-driven electric vehicles with external yaw-moment

Jin, Xin; Yin, Guodong; Zeng, Xiaohua; Chen, Jiansong

doi:10.1016/j.jfranklin.2017.07.006

Cited by 49 publications

(20 citation statements)

References 55 publications

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“…The LQR-based ESC proposed in this article is designed based on a vehicle model that considers roll motion effects on lateral stability. To study the benefits of this approach, a version of the proposed control system was implemented with the LQR gain matrix defined based on a 2DOF linear (9)…”

Section: Dof Linear Modelmentioning

confidence: 99%

“…Due to ESC's proven life-saving effectiveness, advances in control theory and increased computational power available for embedded systems, researches have been performed in the past years to explore in ESC design the benefits of control techniques that require more processing power to be used in real time application, such as Model based Predictive Control (MPC) [5,6,18], Sliding Mode Control (SMC) [11,14,21], backstepping technique [26] and robust gain schedule [8,9]. But advanced application of classical and easy implemented control technique such as Linear Quadratic Regulator (LQR) has not been considered in the same way.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Development and evaluation with MIL and HIL simulations of a LQR-based upper-level electronic stability control

Magalhães

Murilo

Lopes

2019

J Braz. Soc. Mech. Sci. Eng.

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This paper proposes an electronic stability control and shows MIL and HIL simulations performed for evaluation. Two designs are presented, one based on two-degrees-of-freedom linear model that includes side-slip and yaw motion and other based on three-degrees-of-freedom linear model that includes roll motion. Model-in-the-loop and Hardware-in-the-loop simulations were performed to test ESC on vehicle represented by a nonlinear model that considers lateral, yaw and roll motions and an intelligent driver model to generate the steering wheel command as driver reaction to vehicle motion in respect with desired path. It's found from simulations for double lane change maneuver that the proposed controller is effective in reducing of sideslipping, rolling and yaw rate errors, keeping the steering stable in scenarios where the driver loses control of the vehicle, even in presence of disturbances in vehicle response in relation with response predicted by linear model used for control design. Keywords Electronic stability control • Linear quadratic regulator • Hardware-in-the-loop • Vehicle steering dynamic List of symbols a Length from front axis to center of mass b Length from rear axis to center of mass l Vehicle total length from rear axis to front axis t f Front track width t r Rear track width h s Height of center of mass above rolling center h Height of center of mass m s Sprung mass I zz Yawing inertial moment I xx Rolling inertial moment I xz Inertial product related to yawing and rolling c f Front rolling damping coefficient c r Rear rolling damping coefficient k f Front rolling stiffness coefficient k r Rear rolling stiffness coefficient f ∕ Front steer-by-roll coefficient M u Extra yaw moment given as control signal I s Steering coefficient u Vehicle longitudinal speed v Vehicle lateral speed Yaw angle Roll angle f Steering angle of front wheels r Steering angle of rear wheels D Front steer angle due to the driver's steering wheel command F yi Lateral force generated by tire i Camber angle i Tire slip angle of wheel i Vehicle side-slip angle g Gravity acceleration C i Cornering stiffness of wheel i C i Camber stiffness K Camber gradient r ∕ Rear steer-by-roll coefficient Tire-road friction coefficient

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Section: Dof Linear Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Development and evaluation with MIL and HIL simulations of a LQR-based upper-level electronic stability control

Magalhães

Murilo

Lopes

2019

J Braz. Soc. Mech. Sci. Eng.

View full text Add to dashboard Cite

show abstract

“…The gain matrix is then computed as in (19) with the N and Y matrices associated with the smallest γ . By then calculating K from (19) and inserting (16) in the first two equations of (15), a new state-space realisation of the closed-loop system is obtained as…”

Section: Robust Controller Synthesismentioning

confidence: 99%

“…However, the reliability of the LTI tyre model under different driving conditions, especially in evasive manoeuvers (e.g high lateral acceleration manoeuvers), has been a major concern and these models have limitations to represent nonlinear dynamics of the tyres. To deal with the problem of tyre nonlinearity, it is possible to synthesise the robust controller for the uncertain linear vehicle model with tyre cornering stiffness as an uncertain parameter within a known interval [9,[16][17][18]. In order to have a more accurate tyre model and capture some important un-modelled tyre dynamics, the cornering stiffness can also be viewed as a time-varying uncertain parameter [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Robust lateral control of long-combination vehicles under moments of inertia and tyre cornering stiffness uncertainties

Kati

Köroğlu

Fredriksson

2018

Vehicle System Dynamics

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A robust steering-based controller synthesis is presented for an Adouble combination vehicle with a steerable dolly. The controller ensures robust stability and performance in the face of uncertainties in the cornering stiffness of the tyres and the moments of inertia of the semitrailers, which are treated as time-varying and time-invariant parameters respectively. A descriptor-type representation of the system is employed since a standard state-space model depends rationally on the moments of inertia. The controller synthesis is formulated as an H ∞-type static output feedback, which uses information from only one articulation angle. The driver steering input is also used by including a static feed-forward. The proposed synthesis method is based on linear matrix inequality (LMI) optimisation. The controller is verified based on the simulation results obtained from both (approximate) linear and (high-fidelity) nonlinear vehicle models. The results indicate significant improvement in the high-speed lateral performance of the A-double in the presence of parametric uncertainties.

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“…e structure of an electric vehicle driven by in-wheel motors is different from that of traditional vehicles driven by internal combustion engines in that it does not use an engine or transmission, places the motor inside the hub appropriately, and uses a battery as the power supply. e eight in-wheel motor-independent drive electric vehicle (8WIDEV) has eight independent controllable motors, which has the potential to improve the vehicle handling stability [1,2]. e 8WIDEV system is a typical redundantly actuated system and has greater flexibility than four in-wheel motor-independent drive electric vehicles [3].…”

Section: Introductionmentioning

confidence: 99%

Electronic Stability Control for Improving Stability for an Eight In-Wheel Motor-Independent Drive Electric Vehicle

Zhao

Zhang

2019

Shock and Vibration

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An electronic stability control (ESC) based on torque distribution is proposed for an eight in-wheel motor-independent drive electric vehicle (8WIDEV). The proposed ESC is extremely suitable for the independent driving vehicle to enhance its handling stability performance. The vehicle model is established based on a prototype 8WIDEV. A hierarchical control strategy, which includes a reference state generation controller, an upper-level vehicle controller, and a lower-level optimal control allocation controller, is utilized in the ESC. The reference state generation controller is used to obtain the ideal reference vehicle state. The upper-level vehicle controller is structured based on sliding mode control, which obtains the generalized objective force during 8WIDEV movement, therein considering the side slip angle and yaw rate. The lower-level optimal control allocation controller attempts to allocate the vehicle’s objective force in each motor optimally and reasonably. The model is validated by field measurement results under the step input condition and snake input condition. Simulation results from a hardware-in-the-loop (HIL) simulation platform indicate that the ESC based on the optimized allocation proposed for 8WIDEV achieves better stability performance compared with direct yaw moment control (DYC).

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Robust gain-scheduled output feedback yaw stability control for in-wheel-motor-driven electric vehicles with external yaw-moment

Cited by 49 publications

References 55 publications

Development and evaluation with MIL and HIL simulations of a LQR-based upper-level electronic stability control

Development and evaluation with MIL and HIL simulations of a LQR-based upper-level electronic stability control

Robust lateral control of long-combination vehicles under moments of inertia and tyre cornering stiffness uncertainties

Electronic Stability Control for Improving Stability for an Eight In-Wheel Motor-Independent Drive Electric Vehicle

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