The effect of half-shaft torsion dynamics on the performance of a traction control system for electric vehicles

Bottiglione, Francesco; Sorniotti, Aldo; Shead, Leo

doi:10.1177/0954407012440526

Cited by 51 publications

(36 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“… Compute the NLP solution (or recover it from previous steps) at the points of interest.  Compute the mp-QP solution on the whole hyper-rectangle, using the NLP solution at the Chebyshev center plus its coordinates, as the linearization point for the terms in (15)- (18).  Evaluate the mp-QP solution for all the aforementioned points.…”

Section: B Off-line Solutionmentioning

confidence: 99%

“…In parallel to sliding mode control [4] and maximum transmissible torque estimation [5] algorithms, the recent literature (see [6]- [18]) on the topic of ABS and TC shows growing interest in model-based control, with focus on model predictive control (MPC). For example, [6] discusses a gain scheduled linear quadratic regulator (LQR) approach for ABS control, with experimental results on an internal-combustionengine-driven vehicle with electro-mechanical brakes.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Explicit Nonlinear Model Predictive Control for Electric Vehicle Traction Control

Tavernini

Metzler

Gruber

et al. 2019

IEEE Trans. Contr. Syst. Technol.

Self Cite

103

View full text Add to dashboard Cite

Abstract-This study presents a traction control system for electric vehicles with in-wheel motors, based on explicit non-linear model predictive control. The feedback law, available beforehand, is described in detail, together with its variation for different plant conditions. The explicit controller is implemented on a rapid control prototyping unit, which proves the real-time capability of the strategy, with computing times in the order of microseconds. These are significantly lower than the required sampling time for a traction control application. Hence, the explicit model predictive controller can run at the same frequency as a simple traction control system based on Proportional Integral (PI) technology. High-fidelity model simulations provide: i) a performance comparison of the proposed explicit non-linear model predictive controller with a benchmark PI-based traction controller with gain scheduling and anti-windup features; and ii) a performance comparison among two explicit and one implicit non-linear model predictive controllers based on different internal models, with and without consideration of transient tire behavior and load transfers. Experimental test results on an electric vehicle demonstrator are shown for one of the explicit non-linear model predictive controller formulations.Index Terms-traction control, wheel slip, model predictive control, PI control, electric vehicle, in-wheel motors.Sorniotti (email: a.sorniotti@surrey.ac.uk) are with the

show abstract

Section: B Off-line Solutionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Explicit Nonlinear Model Predictive Control for Electric Vehicle Traction Control

Tavernini

Metzler

Gruber

et al. 2019

IEEE Trans. Contr. Syst. Technol.

Self Cite

103

View full text Add to dashboard Cite

show abstract

“…In this application, the in-wheel drivetrains are characterised by very fast dynamics. In fact, the absence of half-shafts prevents any torsional oscillations at the relatively low frequencies relevant to vehicle drivability (Bottiglione et al, 2012). As a consequence, during traction the main possible source of chattering is represented by the tyre dynamics due to the longitudinal relaxation length, L rel (Pacejka, 2006).…”

mentioning

confidence: 99%

Integral sliding mode for the yaw moment control of four-wheel-drive fully electric vehicles with in-wheel motors

Goggia

Sorniotti

Novellis

et al. 2015

IJPT

Self Cite

View full text Add to dashboard Cite

Fully electric vehicles with individually controlled motor drives allow the continuous actuation of direct yaw moment control in order to enhance vehicle safety and the handling performance by achieving a set of reference understeer characteristics. For applications on real vehicles, the control structure must provide ease of implementation, robustness and tunability. This paper discusses an integral sliding mode formulation for torque-vectoring control, which fulfils these requirements. The control structure is presented with reference to the vehicle cornering performance objectives, the motivation for integral sliding mode control and the selection of the controller parameters for stability and chattering avoidance. Six different manoeuvres are simulated for an in-wheel electric motor drivetrain layout. The results show that integral sliding mode control has significant benefits over a more conventional control method based on a combined feedforward and proportional-integral-derivative controller. The integral sliding mode controller does not require fine tuning of a feedforward control action and is characterised by superior tracking performance and disturbance rejection properties. Integral sliding mode for the yaw moment control of four-wheel-drive 389

show abstract

“…19,20 Assuming that the value of the halfshaft torque is available, the error term between the target and the real value of the half-shaft torque can be represented by…”

Section: Sliding-mode-based Control To Compensate For the Powertrain mentioning

confidence: 99%

Mode-switching-based active control of a powertrain system with non-linear backlash and flexibility for an electric vehicle during regenerative deceleration

Zhang

et al. 2014

Proceedings of the Institution of Mechanical Engineers, Part D:

View full text Add to dashboard Cite

Regenerative braking provided by an electric powertrain is very different from conventional friction braking with respect to the system dynamics. During regenerative decelerations, the powertrain backlash and flexibility excite driveline oscillations, causing the vehicle driveability and the blended brake performance to deteriorate. In this article, system models, including a powertrain model with non-linear backlash and flexibility, and a hydraulic brake system model, are developed. The effects of the powertrain backlash and the flexibility on the vehicle driveability during regenerative deceleration are analysed. To improve the driveability and the blended braking performance of an electric vehicle further, a mode-switching-based active control algorithm with a hierarchical architecture is developed providing compensation for the backlash and the flexibility. The proposed control algorithms are simulated and compared with the baseline strategy under the regeneration braking process. The simulation results show that the vehicle driveability and the blended braking performance can be significantly enhanced by the developed active control algorithm.

show abstract

The effect of half-shaft torsion dynamics on the performance of a traction control system for electric vehicles

Cited by 51 publications

References 19 publications

Explicit Nonlinear Model Predictive Control for Electric Vehicle Traction Control

Explicit Nonlinear Model Predictive Control for Electric Vehicle Traction Control

Integral sliding mode for the yaw moment control of four-wheel-drive fully electric vehicles with in-wheel motors

Mode-switching-based active control of a powertrain system with non-linear backlash and flexibility for an electric vehicle during regenerative deceleration

Contact Info

Product

Resources

About