Comparison of Traction Controllers for Electric Vehicles With On-Board Drivetrains

IEEE Trans. Contr. Syst. Technol.

Gruber

et al. 2019

Self Cite

107

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

Section: A Test Scenario and Evaluation Metricsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Explicit Nonlinear Model Predictive Control for Electric Vehicle Traction Control

Tavernini

IEEE Trans. Contr. Syst. Technol.

Gruber

et al. 2019

Self Cite

107

“…The nonlinear model is a development of the one in [37]. In addition to the features of the linear model, the nonlinear model, developed in Matlab-Simulink, includes a nonlinear Pacejka tire model, with tire relaxation length, , dependent on vertical tire load and slip ratio [38]:…”

Section: B Nonlinear Modelmentioning

confidence: 99%

Comparison of Anti-Jerk Controllers for Electric Vehicles With On-Board Motors

Scamarcio

IEEE Trans. Veh. Technol.

Gruber

et al. 2020

Self Cite

Anti-jerk controllers actively suppress the torsional oscillations of automotive drivetrains, caused by abrupt variations of the traction torque. The main benefits are: i) enhanced passengers' comfort; and ii) increased component life. Extensive literature deals with the design of anti-jerk controllers for electric powertrains with on-board motors, i.e., in which the electric motor is part of the sprung mass of the vehicle, and transmits torque to the wheels through a transmission, half-shafts and constant velocity joints. Nevertheless, a complete and structured comparison of the performance of the different control options is still missing. This study addresses the gap through the assessment of six anti-jerk controllersfive exemplary formulations from the literature, and one novel formulation based on explicit nonlinear model predictive control (eNMPC). All proposed control structures have the potential to be implemented on production vehicles. A set of objective performance indicators is defined to assess the controllers, which are tuned through an optimizationbased routine. Results show that the wheel speed input is critical to enhance controller performance, but may lead to reduced robustness.

“…EHB technology, similarly to electro-mechanical brake technology, permits more refined wheel slip controllers with continuous brake torque modulation [9]. Algorithms based on proportional integral derivative (PID) formulations [10,11], second order sliding mode [12] as well as maximum transmissible torque estimation [13] have been proposed for ABS or traction control. [14] discusses a selection of wheel slip controllers for electric vehicles, not requiring vehicle speed detection, while [15] presents slip controllers for split-conditions.…”

Section: Introductionmentioning

confidence: 99%

“…The eNMPC ABS of this research prepares the ground for these developments, as the tire-road friction coefficient can be included as an input parameter varying in real-time.  NMPC for ABS control offers benefits with respect to alternative control technologies, such as H∞ and sliding mode control [10]. The main issue of H∞ control is that the range of variation of the longitudinal tire slip stiffness is too wide to be captured by a single controller based on a linear model with a fixed longitudinal slip stiffness.…”

mentioning

confidence: 99%

An Explicit Nonlinear Model Predictive ABS Controller for Electro-Hydraulic Braking Systems

Tavernini

Vacca

IEEE Trans. Ind. Electron.

et al. 2020

Self Cite

This study addresses the development and Hardware-in-the-Loop (HiL) testing of an explicit nonlinear model predictive controller (eNMPC) for an anti-lock braking system (ABS) for passenger cars, actuated through an electro-hydraulic braking (EHB) unit. The control structure includes a compensation strategy to guard against performance degradation due to actuation dead times, identified through experimental tests. The eNMPC is run on an automotive rapid control prototyping unit, which shows its real-time capability with comfortable margin. A validated high-fidelity vehicle simulation model is used for the assessment of the ABS on a HiL rig equipped with the braking system hardware. The eNMPC is tested in 7 emergency braking scenarios, and its performance is benchmarked against a proportional integral derivative (PID) controller. The eNMPC results show: i) the control system robustness with respect to variations of tire-road friction condition and initial vehicle speed; and ii) a consistent and significant improvement of the stopping distance and wheel slip reference tracking, with respect to the vehicle with the PID ABS.