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Multi-Level Energy Management for Hybrid Electric Vehicles—Part I
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Multi-Level Energy Management—Part II: Implementation and Validation

1
Department of Mechanical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands
2
DAF Trucks N.V., 5600 PT Eindhoven, The Netherlands
*
Author to whom correspondence should be addressed.
vehicles 2019, 1(1), 41-56; https://doi.org/10.3390/vehicles1010003
Received: 2 October 2018 / Revised: 21 January 2019 / Accepted: 22 January 2019 / Published: 15 February 2019
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Abstract

In hybrid electric vehicles, energy management systems (EMS) using optimization show superior fuel efficiency compared to rule-based strategies. However, little research shows its real-life applicability. In Part II of this work, the multi-level, model-predictive EMS from Part I is implemented on a heavy-duty parallel hybrid electric vehicle, using GPS and map data as preview. The power split, hybrid mode, and gear selection, including switching costs, are optimized in real time, thereby proving the feasibility of optimal control techniques for hybrid driveline control. Functional validation of the EMS on a test track confirm the fuel-saving mechanism as simulated in Part I. In addition to a fuel saving of 36%, the EMS also improves the drivability, by reducing the amount of open driveline events. View Full-Text
Keywords: energy management; optimal control; multi-level; switching decisions energy management; optimal control; multi-level; switching decisions
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van Reeven, V.; Hofman, T. Multi-Level Energy Management—Part II: Implementation and Validation. vehicles 2019, 1, 41-56.

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