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Simulation Tools for Predicting Energy Consumption and Range of Electric Two-wheelers

Lord, Nathan
http://rave.ohiolink.edu/etdc/view?acc_num=osu1468844436

Abstract Details

2016, Master of Science, Ohio State University, Mechanical Engineering.
This research investigates the design and implementation of simulation tools used to predict the energy consumption and range of electric two-wheelers. The simulation tools developed can be used as design tools or as a real-time prediction of available range. These simulation tools can be used to design electric motorcycles which could decrease traffic congestion and pollution in urban areas. The first simulator was developed in collaboration with GenZe to develop a simulation tool to help design their next electric scooter. The equations for each component were developed to accurately estimate the energy consumption of the first GenZe scooter and developed to be modular in order to be used as a design tool in the future. Each component of the simulator was calibrated to the current GenZe scooter by conducting multiple experiments on the individual components and full vehicle testing. The motor and inverter models were calibrated using data collected at the Center for Automotive Research (CAR) using a dynamometer and a power analyzer. The data collected was used to find the motor constants and efficiency of the motor and inverter. The battery model was calibrated using a battery tester and a environmental chamber at CAR. The data collected was used to find the internal resistance and first-order equivalent circuit RC parameters of a single cell at multiple states of charge and temperatures. The electric powertrain model and the full GenZe model were validated using a chassis dynamometer and riding the scooter at the Transportation Research Center. The electric powertrain model was validated with low error between the predicted results and data collected on a chassis dynamometer which met the requirements of the GenZe project. Errors were found between the full GenZe model and collected data from riding the scooter on the road which suggested the chassis model does not accurately predict energy consumption during turning. In light of the limitations seen in the GenZe model an investigation into two-dimensional vehicle dynamics modeling was conducted. Two additional chassis models were developed to model a turning two-wheeler. The first model predicts the two-dimensional location of the vehicle by estimating the lateral tire forces on the motorcycle. The second model extends the first model by estimating the lean of the motorcycle given the speed and corner radius. The predicted energy consumption of the two models and the GenZe chassis model were compared to BikeSim through multiple turning profiles. It was found the models underestimate the energy consumption compared to BikeSim, which suggested the models do not predict all the forces that slow a two-wheeler during turning. Further comparison between the models and BikeSim shows a difference between the predicted normal forces on the tires and the rear tire radius suggesting future work should investigate the pitching and tire dynamics of a two-wheeler during turning. This work uncovers the complexity of estimating the road forces on a two-wheeler. Ultimately future work should focus on the road forces of two-wheelers in order to increase the accuracy of energy consumption prediction of electric motorcycle simulation tools.
Marcello Canova (Advisor)
Giorgio Rizzoni (Committee Member)
130 p.
Mechanical Engineering

Recommended Citations

Citations

  • Lord, N. (2016). Simulation Tools for Predicting Energy Consumption and Range of Electric Two-wheelers [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1468844436

    APA Style (7th edition)

  • Lord, Nathan. Simulation Tools for Predicting Energy Consumption and Range of Electric Two-wheelers. 2016. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1468844436.

    MLA Style (8th edition)

  • Lord, Nathan. "Simulation Tools for Predicting Energy Consumption and Range of Electric Two-wheelers." Master's thesis, Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1468844436

    Chicago Manual of Style (17th edition)

osu1468844436
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© 2016, all rights reserved.
This open access ETD is published by The Ohio State University and OhioLINK.