Simulation Tools For Predicting Energy Consumption And Range Of Electric Two Wheelers
Download Simulation Tools For Predicting Energy Consumption And Range Of Electric Two Wheelers PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Simulation Tools For Predicting Energy Consumption And Range Of Electric Two Wheelers book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Simulation Tools for Predicting Energy Consumption and Range of Electric Two-wheelers
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.
Methods and Applications for Modeling and Simulation of Complex Systems
This book constitutes the refereed proceedings of the 22nd Asia Simulation Conference on Methods and Applications for Modeling and Simulation of Complex Systems, AsiaSim 2023, held in Langkawi, Malaysia, during October 25–26, 2023. The 77 full papers included in this book were carefully reviewed and selected from 164 submissions. They were organized in topical sections as follows: Modelling and Simulation, Artificial intelligence, Industry 4.0, Digital Twins Modelling, Simulation and Gaming, Simulation for Engineering, Simulation for Sustainable Development, Simulation in Social Sciences.
Data Science and Simulation in Transportation Research
Given its effective techniques and theories from various sources and fields, data science is playing a vital role in transportation research and the consequences of the inevitable switch to electronic vehicles. This fundamental insight provides a step towards the solution of this important challenge. Data Science and Simulation in Transportation Research highlights entirely new and detailed spatial-temporal micro-simulation methodologies for human mobility and the emerging dynamics of our society. Bringing together novel ideas grounded in big data from various data mining and transportation science sources, this book is an essential tool for professionals, students, and researchers in the fields of transportation research and data mining.