A model predictive control allocation approach to hybrid braking of electric vehicles

Satzger, Clemens; Castro, Ricardo Pinto de; Bünte, Tilman

doi:10.1109/ivs.2014.6856529

Cited by 26 publications

(15 citation statements)

References 13 publications

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“…Where A d and B d are filled with the discretized parameters a i and b i respectively according to equations (11) and (12). The limits imposed to u are due to the friction ellipse [15], while the limits imposed to δ are due to the actuators' saturations.…”

Section: B Model Predictive Control Theory For Control Allocationmentioning

confidence: 99%

“…Finally, one major difference with respect to other researches in MPCA [11], [12], [20], is the solver used to solve the problem. In most of these researches, the computation effort constitute one of the major drawbacks.…”

Section: B Model Predictive Control Theory For Control Allocationmentioning

confidence: 99%

“…The delay can be taken into account in the whole prediction horizon to determine when the control request should be submitted. In this context, MPCA has been used in [11] to coordinate Hybrid Braking in electric vehicles. Results showed that the MPCA can offer faster transient response, without compromising the energy recuperation efficiency of the actuators.…”

Section: Introductionmentioning

confidence: 99%

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Model Predictive Control Allocation of Systems with Different Dynamics

Kissai

Monsuez

Mouton

et al. 2019

2019 IEEE Intelligent Transportation Systems Conference (ITSC)

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Several systems are integrated in passenger cars. Some of them are just redundant systems due to safety requirements. Others, are completely different and can interact with each other as long as they are operating inside the same vehicle. Control allocation methods have been successfully implemented in advanced aircrafts to avoid conflicts, especially in the context of redundant systems. In this paper, we will rather focus on coordinating non-redundant advanced chassis systems with different dynamics. This difference in dynamics can be especially problematic when systems exhibit different communication delays. Model Predictive Control Allocation (MPCA) methods are therefore investigated in order to activate the right system at the right moment. Results show that particularly when the most effective system is saturated, another system with a different time delay can be activated few steps before saturation to instantly take over the maneuver. With good knowledge of actuator dynamics and higher computation power, MPCA methods are able to solve complex problems in severe situations.

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Section: B Model Predictive Control Theory For Control Allocationmentioning

confidence: 99%

Section: B Model Predictive Control Theory For Control Allocationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Model Predictive Control Allocation of Systems with Different Dynamics

Kissai

Monsuez

Mouton

et al. 2019

2019 IEEE Intelligent Transportation Systems Conference (ITSC)

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“…The proposed approach achieves robustness in wheel slip tracking in the presence of tyre-road friction variations by incorporating an adaptive slip control algorithm. A linear Model Predictive Control (MPC) method is proposed for the torque allocation to work along with a linear slip controller in [21]. This approach still requires an independent slip control algorithm to determine commanded ABS torque before the allocation procedure can take place.…”

Section: Introductionmentioning

confidence: 99%

“…A combined slip control and torque allocation algorithm using linear MPC is presented in [22]. The authors demonstrate the enhanced performance of the controller compared to cascaded control approaches, as in [9] and [21]. The MPC controller of [22] uses a low order internal model of slip dynamics, which is linearised with respect to the desired equilibrium condition, assuming slowly varying speed when compared to wheel slip variations.…”

Section: Introductionmentioning

confidence: 99%

Wheel slip control with torque blending using linear and nonlinear model predictive control

Basrah

Siampis

Velenis

et al. 2017

Vehicle System Dynamics

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Modern Hybrid Electric Vehicles employ electric braking to recuperate energy during deceleration. However, currently Anti-lock Braking System (ABS) functionality is delivered solely by friction brakes. Hence regenerative braking is typically deactivated at a low deceleration threshold in case high slip develops at the wheels and ABS activation is required. If blending of friction and electric braking can be achieved during ABS events, there would be no need to impose conservative thresholds for deactivation of regenerative braking and the recuperation capacity of the vehicle would increase significantly. In addition, electric actuators are typically significantly faster responding and would deliver better control of wheel slip than friction brakes. In this work we present a control strategy for ABS on a fully electric vehicle with each wheel independently driven by an electric machine and friction brake independently applied at each wheel. In particular we develop linear and nonlinear model predictive control strategies for optimal performance and enforcement of critical control and state constraints. The capability for real time implementation of these controllers is assessed and their performance is validated in high fidelity simulation.

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Mitigation of transient torque reversals in indirect drive wind turbine drivetrains

2023

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Bearing failure in wind turbine gearboxes is one of the significant sources of downtime. While it is well-known that bearing failures cause the largest downtime, the failure cause(s) is often elusive. The bearings are designed to satisfy their rolling contact fatigue (RCF) life. However, they often undergo sudden and rapid failure within a few years of operation. It is well-known that these premature failures are attributed to surface damages such as white surface flaking (WSF), white etching cracks (WECs) and axial cracks. In that regard, transient torque reversals (TTRs) in the drivetrain have emerged as one of the primary triggers of surface damage, as explained in this paper.The risk associated with TTRs motivates the need to mitigate TTRs arising in the drivetrain due to various transient events. This paper investigates three TTR mitigation methods. First, two existing devices, namely, the torsional tuned mass damper and the asymmetric torque limiter, are studied to demonstrate their TTR mitigation capabilities. Then, a novel idea of open-loop high-speed shaft mechanical brake control is proposed. The results presented here show that while the torsional tuned mass damper and the asymmetric torque limiter can improve the torsional vibration characteristics of the drivetrain, they cannot mitigate TTRs in terms of eliminating the bearing slip risk associated with TTRs. However, the novel approach proposed here can mitigate TTRs both in terms of improving the torque characteristic in the high-speed shaft and reducing the risk of bearing slip by actuating the high-speed shaft brake at the onset of the transient event. Furthermore, the control method is capable of mitigating TTRs with the mechanical limitations of a pneumatic actuator in terms of bandwidth and initial dead time applied to it. This novel approach allows the wind turbines to protect the gearbox bearings from TTRs using the existing hardware on the turbine.

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A model predictive control allocation approach to hybrid braking of electric vehicles

Cited by 26 publications

References 13 publications

Model Predictive Control Allocation of Systems with Different Dynamics

Model Predictive Control Allocation of Systems with Different Dynamics

Wheel slip control with torque blending using linear and nonlinear model predictive control

Mitigation of transient torque reversals in indirect drive wind turbine drivetrains

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