EPSRC Reference: |
GR/R19946/01 |
Title: |
Model Predictive Control For Energy Management In All/More-Electric Vehicles |
Principal Investigator: |
Bingham, Professor CM |
Other Investigators: |
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Researcher Co-Investigators: |
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Project Partners: |
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Department: |
Electronic and Electrical Engineering |
Organisation: |
University of Sheffield |
Scheme: |
Fast Stream |
Starts: |
15 October 2001 |
Ends: |
14 April 2003 |
Value (£): |
65,313
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EPSRC Research Topic Classifications: |
Electric Motor & Drive Systems |
Energy Efficiency |
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EPSRC Industrial Sector Classifications: |
Energy |
Transport Systems and Vehicles |
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Related Grants: |
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Panel History: |
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Summary on Grant Application Form |
Methodologies currently employed for energy management in electric vehicles are generally the result of extensive experimental trials and iterative modifications, resulting in map-based empirical solutions which have limited flexibility to cope with different driving styles and driving cycles, or the real-time macro-dynamics of the power-train that can have a significant effect on the long-term economic tilisation of the energy storage components.This proposal is concerned with the development of predictor-based optimal energy management strategies to accommodate long-term economic as well as performance requirements of all-electric and hybrid-electric vehicles. The research programme embraces the development of power conservative simulation models of all-electric and dual-source hybrid drive-train topologies; identification and assessment of model-predictive control techniques for optimal energy management; analysis of the effects of different prediction horizons on the dynamic performance, efficiency, and economic operation of the drive-train; and preliminary investigations of component stresses within the power train.The findings will be validated on an existing brass-board demonstrator of an all-electric vehicle drive-train equipped with multiple energy sources.
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Key Findings |
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Potential use in non-academic contexts |
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Impacts |
Description |
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Summary |
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Date Materialised |
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Sectors submitted by the Researcher |
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Project URL: |
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Further Information: |
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Organisation Website: |
http://www.shef.ac.uk |