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Optimum design of series hybrid electric buses by genetic algorithm

Hasanzadeh, A ; Sharif University of Technology | 2005

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  1. Type of Document: Article
  2. DOI: 10.1109/ISIE.2005.1529148
  3. Publisher: 2005
  4. Abstract:
  5. In this paper, a new software is introduced that is developed to give the most appropriate solution for the component selection and design of a hybrid electric bus. There are several simulation programs that can simulate behavior of a hybrid electric bus, but most of them are not able to suggest the best design and the best choice of the components. Customer requirements are dissimilar and there are several different parameters that they may need. Cost, pollution, driving cycle, battery type, DC link voltage, weight, volume, fuel consumption, and acceleration are some parameters that vary from one customer to the other. The stated software that is developed and presented by this paper will generate a list of the best choices to the user. By this, one can optimize the HEV bus design based on the customer requirements and his parameters. The weight of a certain parameter in the cost function for optimization may be modified if the customer is not satisfied. This software uses the genetic algorithm for this optimization. Genetic chains are created and the best ones that are suitable and are close to the customer needs are chosen. Then the system is simulated by ADVISOR (Advanced Vehicle Simulator) program that is written by NREL (National renewable Energy Laboratory of the America). © 2005 IEEE
  6. Keywords:
  7. Computer simulation ; Computer software ; Electric potential ; Genetic algorithms ; Optimal control systems ; Problem solving ; Systems analysis ; Advanced Vehicle Simulators ; Customer requirements ; DC link voltage ; Driving cycle ; Hybrid electric buses ; Electric vehicles
  8. Source: IEEE International Symposium on Industrial Electronics 2005, ISIE 2005, Dubrovnik, 20 June 2005 through 23 June 2005 ; Volume IV , 2005 , Pages 1465-1470 ; 0780387384 (ISBN); 9780780387386 (ISBN)
  9. URL: https://ieeexplore.ieee.org/document/1529148