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Finding an Optimal Driving Strategy for an Electric Bus Based on Operational Data

[+] Author Affiliations
Warren Vaz, Arup K. Nandi, Umit O. Koylu

Missouri University of Science and Technology, Rolla, MO

Paper No. ES2015-49089, pp. V002T16A001; 9 pages
doi:10.1115/ES2015-49089
From:
  • ASME 2015 9th International Conference on Energy Sustainability collocated with the ASME 2015 Power Conference, the ASME 2015 13th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2015 Nuclear Forum
  • Volume 2: Photovoltaics; Renewable-Non-Renewable Hybrid Power System; Smart Grid, Micro-Grid Concepts; Energy Storage; Solar Chemistry; Solar Heating and Cooling; Sustainable Cities and Communities, Transportation; Symposium on Integrated/Sustainable Building Equipment and Systems; Thermofluid Analysis of Energy Systems Including Exergy and Thermoeconomics; Wind Energy Systems and Technologies
  • San Diego, California, USA, June 28–July 2, 2015
  • Conference Sponsors: Advanced Energy Systems Division, Solar Energy Division
  • ISBN: 978-0-7918-5685-7
  • Copyright © 2015 by ASME

abstract

One of the clean energy initiatives at Missouri S&T is an electric shuttle bus service, the Ebus. It provides valuable operational data for a fleet-type electric vehicle (EV) operating over a fixed route. The primary aim of this study is to use the daily operational data obtained from the Ebus in order to formulate an optimal driving strategy. Existing research efforts to improve EVs focus on improvements to the architecture and the energy management strategy. However, they fail to provide the driver with an optimal driving strategy leading to suboptimal use of the stored battery energy. This shortcoming was addressed here by implementing a multi-objective approach to find an optimal driving strategy for an electric bus. The driving strategy was taken to comprise two parts: a constant trip speed and an acceleration value to achieve that speed. From the operational data, the efficiency and power consumption of the electric motor were computed for different speeds. By assuming the entire trip was executed at a constant speed, the range for each speed was calculated. The speeds were ranked based on their corresponding ranges. Then, to achieve the optimal speed, the acceleration duration and energy consumption for different acceleration values were computed. The values were ranked based on the trade-off between duration and energy. The choice of driving strategy (exact speed and acceleration values) is left to the driver since different strategies would be needed for different road conditions. This multi-objective approach gives flexibility to the driver and promotes optimal use of the stored battery energy, thereby enhancing the energy efficiency and range of the Ebus. It can be easily implemented in other electric vehicles as well.

Copyright © 2015 by ASME

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