Energy optimal control of an over actuated Robotic Electric Vehicle using enhanced control allocation approaches

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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A Framework for Optimal Control Allocation with Structural Load Constraints

AIAA Atmospheric Flight Mechanics Conference ◽

10.2514/6.2010-8112 ◽

2010 ◽

Cited By ~ 5

Author(s):

Susan Frost ◽

Brian Taylor ◽

Christine Jutte ◽

John Burken ◽

Khanh Trinh ◽

...

Keyword(s):

Optimal Control ◽

Control Allocation

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Optimal control of an electromagnetic power-split hybrid electric vehicle

Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering ◽

10.1177/0954407012464858 ◽

2012 ◽

Vol 227 (6) ◽

pp. 822-841 ◽

Cited By ~ 4

Author(s):

Haisheng Yu ◽

Jianwu Zhang ◽

Tong Zhang ◽

Xiaolin Tang

Keyword(s):

Optimal Control ◽

Electric Vehicle ◽

Hybrid Electric Vehicle ◽

Electromagnetic Power ◽

Power Split ◽

Hybrid Electric

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Sensitivity Analysis of the Battery Model for Model Predictive Control: Implementable to a Plug-In Hybrid Electric Vehicle

World Electric Vehicle Journal ◽

10.3390/wevj9040045 ◽

2018 ◽

Vol 9 (4) ◽

pp. 45 ◽

Cited By ~ 3

Author(s):

Nicolas Sockeel ◽

Jian Shi ◽

Masood Shahverdi ◽

Michael Mazzola

Keyword(s):

Optimal Control ◽

Model Predictive Control ◽

Fuel Consumption ◽

Electric Vehicle ◽

Predictive Control ◽

Hybrid Electric Vehicle ◽

Control Solution ◽

Current Time ◽

Battery Model ◽

Hybrid Electric

Developing an efficient online predictive modeling system (PMS) is a major issue in the field of electrified vehicles as it can help reduce fuel consumption, greenhouse gasses (GHG) emission, but also the aging of power-train components, such as the battery. For this manuscript, a model predictive control (MPC) has been considered as PMS. This control design has been defined as an optimization problem that uses the projected system behaviors over a finite prediction horizon to determine the optimal control solution for the current time instant. In this manuscript, the MPC controller intents to diminish simultaneously the battery aging and the equivalent fuel consumption. The main contribution of this manuscript is to evaluate numerically the impacts of the vehicle battery model on the MPC optimal control solution when the plug hybrid electric vehicle (PHEV) is in the battery charge sustaining mode. Results show that the higher fidelity model improves the capability of accurately predicting the battery aging.

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