This paper presents gain scheduling of control strategy for parallel hybrid electric vehicles based on the traffic condition. Electric assist control strategy (EACS) is employed with different parameters for different traffic conditions. The parameters of the EACS are optimized and scheduled for different traffic conditions of TEH-CAR driving cycle. TEH-CAR is a driving cycle which is developed based on the experimental data collected from the real traffic condition in the city of Tehran. The objective of the optimization is to minimize the fuel consumption and emissions over the driving cycle, while enhancing or maintaining the driving performance characteristics of the vehicle. Genetic algorithm (GA) is used to solve the optimization problem and the constraints are handled by using penalty functions. The results from the computer simulation show the effectiveness of the approach and reduction in fuel consumption and emissions, while ensuring that the vehicle performance is not sacrificed.
- Design Engineering Division and Computers and Information in Engineering Division
Traffic Condition-Based Gain Scheduling of Electric Assist Control Strategy for Parallel Hybrid Electric Vehicles
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Poursamad, A. "Traffic Condition-Based Gain Scheduling of Electric Assist Control Strategy for Parallel Hybrid Electric Vehicles." Proceedings of the ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 3: 19th International Conference on Design Theory and Methodology; 1st International Conference on Micro- and Nanosystems; and 9th International Conference on Advanced Vehicle Tire Technologies, Parts A and B. Las Vegas, Nevada, USA. September 4–7, 2007. pp. 1083-1090. ASME. https://doi.org/10.1115/DETC2007-34271
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