Electric rear axle torque vectoring for combined yaw stability and velocity control near the limit of handling

Siampis, Efstathios; Massaro, Matteo; Velenis, Efstathios

doi:10.1109/cdc.2013.6760103

Cited by 25 publications

(34 citation statements)

References 6 publications

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“…The formulation is similar to the one found in [1,14], where the interested reader can refer to for more details.…”

Section: Vehicle Model and Reference Generationmentioning

confidence: 97%

“…In the section to follow we compare the two MPC strategies against each other and against an LQR strategy [1] under different scenarios using the full four-wheel model (1) in Simulink Downloaded by [New York University] at 10:28 21 July 2015 environment. We also investigate the changes in tracking performance and computational time when a control horizon that is shorter than the prediction horizon is used.…”

Section: Comparison Of the Two Mpc Strategiesmentioning

confidence: 99%

“…[1] The necessity for velocity regulation in such cases is already mentioned by van Zanten [2] who points out that especially in the case of J-turns, where the turning radius is reduced continuously along the trajectory (a scenario typical on highway exits), the electronic stability control (ESC) yaw moment correction on the lateral dynamics alone is not sufficient. This early remark on the importance of longitudinal control was later realised as one of the ESC new functions in [3], where correction of terminal understeer behaviour is achieved by superimposing individual braking of all four wheels on the standard ESC intervention.…”

Section: Introductionmentioning

confidence: 98%

“…In [6] a controller providing decoupled longitudinal force and yaw moment inputs at the higher level is combined with a static control allocation scheme to calculate forces and actuator inputs. In [1] address velocity, yaw and sideslip regulation in terminal understeer is presented. Simulation results using a driver model in a U-turn scenario show that the controller not only keeps the vehicle within the road boundaries, but also allows for a smoother negotiation of the corner with less steering effort from the driver.…”

Section: Introductionmentioning

confidence: 99%

“…Since the main disadvantage of using an MPC strategy is the computational effort attached to it, two MPC strategies of different complexity are then constructed: (1) one using the full vehicle model and (2) on the performance and the computational load of each strategy are then analysed. Finally, the two strategies are compared against each other in Simulink environment and against a linear quadratic regulator (LQR) strategy [1] in CarSim environment.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Rear wheel torque vectoring model predictive control with velocity regulation for electric vehicles

Siampis

Velenis

Longo

2015

Vehicle System Dynamics

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In this paper we propose a constrained optimal control architecture for combined velocity, yaw and sideslip regulation for stabilisation of the vehicle near the limit of lateral acceleration using the rear axle electric torque vectoring configuration of an electric vehicle. A nonlinear vehicle and tyre model are used to find reference steady-state cornering conditions and design two model predictive control (MPC) strategies of different levels of fidelity: one that uses a linearised version of the full vehicle model with the rear wheels' torques as the input, and another one that neglects the wheel dynamics and uses the rear wheels' slips as the input instead. After analysing the relative trade-offs between performance and computational effort, we compare the two MPC strategies against each other and against an unconstrained optimal control strategy in Simulink and Carsim environment.

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“…The formulation is similar to the one found in [1,14], where the interested reader can refer to for more details.…”

Section: Vehicle Model and Reference Generationmentioning

confidence: 97%

Section: Comparison Of the Two Mpc Strategiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Rear wheel torque vectoring model predictive control with velocity regulation for electric vehicles

Siampis

Velenis

Longo

2015

Vehicle System Dynamics

Self Cite

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Fundamentals on Vehicle and Tyre Modelling

Kissai

2021

Vehicle Dynamics

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Many books provide vehicle dynamics and tire dynamics equations. Most of them are either too complex or too simplified for global Vehicle Motion Control (VMC). This chapter is focusing on the couplings that exist between longitudinal, lateral and vertical dynamics at both the vehicle and tire level. The equations provided are simple but sufficient for global VMC. Several research papers and industrial patents tend to provide a control strategy for a standalone system. Simplified car models are taken into consideration from the beginning. As we are steering towards global VMC, more complex models are needed. Here, we start from complex equations that are simplified enough to facilitate control synthesis while capturing the required couplings for a coordinated control. Results show how this simplified global dynamics equations are close enough to more complex high-fidelity models. These equations should be therefore used for the next generation of global VMC.Car manufacturers and equipment suppliers are constantly proposing new attractive subsystems to stand out from their competitors. Recently, a large interest has been given particularly to automated vehicles. Automation promises indeed safer and smarter vehicles. Several researches have been carried out on one hand in robotic vision, sensor fusion, decision algorithms, big data management, and others. On the other hand, car manufacturers are looking closely on the over-actuation of the vehicle itself (Shyrokau & Wang, 2012;Soltani, 2014;Sriharsha, 2016). Indeed, giving the vehicle new features such as the ability of steering the rear wheels (Seongjin, 2015), distributing the brake torques or/and the engine torques differently between left and right tires (Siampis et al., 2013) and so on, can expand the vehicle's performance and generate new motion possibilities and car behaviors. This can be actually achieved provided that a global chassis control strategy can be designed.

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Simulation investigation of tractive energy conservation for a cornering rear-wheel-independent-drive electric vehicle through torque vectoring

Sun

Wang

et al. 2017

Sci. China Technol. Sci.

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Electric rear axle torque vectoring for combined yaw stability and velocity control near the limit of handling

Cited by 25 publications

References 6 publications

Rear wheel torque vectoring model predictive control with velocity regulation for electric vehicles

Rear wheel torque vectoring model predictive control with velocity regulation for electric vehicles

Fundamentals on Vehicle and Tyre Modelling

Simulation investigation of tractive energy conservation for a cornering rear-wheel-independent-drive electric vehicle through torque vectoring

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