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Evaluation of optimal state of charge planning using MPC

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conference contribution
posted on 2022-08-16, 13:13 authored by Temiloluwa Jegede, James KnowlesJames Knowles, Thomas SteffenThomas Steffen, Marco D'Amato, Othman Maganga
Hybrid technologies enable the reduction of noxious tailpipe emissions and conformance with ever-decreasing allowable homologation limits. The complexity of the hybrid powertrain technology leads to an energy management problem with multiple energy sinks and sources comprising the system resulting in a high-dimensional time dependent problem for which many solutions have been proposed. Methods that rely on accurate predictions of potential vehicle operations are demonstrably more optimal when compared to rule-based methodology [1]. In this paper, a previously proposed energy management strategy based on an offline optimization using dynamic programming is investigated. This is then coupled with an online model predictive control strategy to follow the predetermined optimal battery state of charge trajectory prescribed by the dynamic program. This work explores the effects of drive cycle segmentation and simplification on the optimality of the results and investigates the effect of reduced prediction accuracy on the optimality of the MPC controller. As the dynamic program relies on future predictions of speed and load, potentially provided from navigation data, the actual drive cycle is likely to vary from the prediction used to perform the offline optimization. The test vehicle modelled in Simulink is a P2 parallel hybrid configuration based on experimental powertrain data. The results of the analysis are then compared to the globally optimal solution using key performance criteria like fuel and energy consumption. Our investigation shows that the energy consumption increase due to poorer prediction accuracy can be up to 19% of the optimal value but also shows that the robustness of the strategy is more acceptable provided certain features of the driveline input can be predicted with a certain degree of accuracy.

Funding

Engineering and Physical Sciences Research Council (EPSRC)

Jaguar Land Rover Ltd.

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

SAE Technical Papers

Source

WCX SAE World Congress Experience

Publisher

SAE International

Version

  • AM (Accepted Manuscript)

Rights holder

© SAE International

Publisher statement

This is a conference paper published by SAE International. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of SAE International.

Acceptance date

2022-01-06

Publication date

2022-03-29

Copyright date

2022

ISSN

0148-7191

eISSN

0096-5170

Language

  • en

Depositor

Dr James Knowles. Deposit date: 16 August 2022

Article number

2022-01-0742

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