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Discrete Grid Optimization of a Rule-Based Energy Management Strategy for a Formula Hybrid Electric Vehicle
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 14, 2015 by SAE International in United States
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Fuel economy and energy consumption in hybrid electric powertrain vehicles are highly dependent on managing power flow requirements. This opportunity has been minimally addressed in previous vehicles entered in the Formula Hybrid SAE competition. This paper outlines a method for determining an optimal rule-based energy management strategy for a post-transmission parallel hybrid electric vehicle developed at the University of Idaho. A supervisory controller determines the proper power split ratio between the available power sources (electrical and thermal). A GT-Suite model was used to simulate powertrain performance based on inputs of a numerically predicted engine performance map, an electric motor characteristic curve, vehicle data, road load parameters derived from a roll-down test, and vehicle driving cycle. The controller parameters included a switching speed below which the vehicle operated in electric mode (unless the battery state of charge was too low) and a power split ratio above the switching speed (provided the battery state of charge was adequate). The Artemis driving cycle which has an average speed of 30 mph and resembles the endurance course in the SAE Formula Hybrid competition, was the basis for the optimization study. Convergence was achieved in 272 iterations and resulted in a switching speed of 17.8 mph and a power split ratio above the switching speed of 24.5% electric energy and 75.5% thermal energy. This resulted in a 15% increase in fuel economy compared to a 50:50 energy split at all vehicle speeds. The optimization method is easily adaptable to other powertrain configurations and driving cycles, including the use of multiple switching speeds that would dynamically adjust the power split ratio.
CitationAsfoor, M., Beyerlein, S., Lilley, R., and Santora, M., "Discrete Grid Optimization of a Rule-Based Energy Management Strategy for a Formula Hybrid Electric Vehicle," SAE Technical Paper 2015-01-1212, 2015, https://doi.org/10.4271/2015-01-1212.
- Zhang X. and Mi C. Vehicle Power Management: Modeling, Control and Optimization First Springer 2011
- Ehsani M. , Gao Y. , and Emadi A. Modern Electric, Hybrid Electric, and Fuel Cell Vehicles: Fundamentals, Theory, and Design CRC Press 2010
- Chau K. and Wong Y. Overview of Power Management in Hybrid Electric Vehicles Energy Conversion and Management 43 15 1953 1968 Oct. 2002
- Cordon , D. , Wos , S. , Beyerlein , S. , and Odom , E. Highly Integrated Parallel Hybrid Powertrain SAE Technical Paper 2012-32-0026 2012 10.4271/2012-32-0026
- Wos S. H. Hybrid vehicle mathematical modeling & drive cycle simulation University of Idaho 2013
- Butsick B. P. Design and mathematical modeling of a hybrid FSAE drivetrain University of Idaho 2011
- Bashford B. Electric propulsion subsystem for a parallel-drive formula hybrid vehicle University of Idaho 2012
- Rinker D. Use of a TK Solver Performance Model in the Design and Testing of a Formula Hybrid Racecar University of Idaho 2013
- Formula-Hybrid-2014-Rules SAE International
- Cuddihy J. A User-Friendly, Two-Zone Heat Release Model for Predicting Spark-Ignition Engine Performance and Emissions University of Idaho 2014
- GT-Suite General and Advanced Simulation Application Manual. Gamma Technologies
- Asfoor M. Sh. Development and Optimization of a Rule-Based Energy Management Strategy for Fuel Economy Improvement in Hybrid electric Vehicles University of Idaho 2014
- Lilley , R. , Asfoor , M. , Santora , M. , Cordon , D. et al. Design of the University of Idaho Formula Hybrid Vehicle SAE Technical Paper 2015-01-0414 2015 10.4271/2015-01-0414