Range prediction estimation for electric vehicles

• Main Author: Ng, Zong Jie.
• Other Authors: School of Computer Engineering
• Format: Final Year Project
• Language: English
• Published: 2013
• Subjects: DRNTU::Engineering::Computer science and engineering::Software::Programming languages; DRNTU::Engineering::Computer science and engineering::Software::Programming techniques
• Online Access: http://hdl.handle.net/10356/51965
• Institution: Nanyang Technological University

With the rapid-growing technologies, navigation system making use of Global Positioning System (GPS) has been made available in various forms. One of the forms includes handheld devices dedicated for navigation purpose where the device has a GPS receiver and a downloaded offline map. For convenience benefits, navigation system was made available even on smartphones and tablets with an additional capability to use WiFi as a stand in for GPS to acquire the current position of the user as well as to provide navigation. TUM CREATE is a research programme aiming to design and build the world’s first purpose-built Electric Taxi. Due to the fact that Electric Vehicles (EVs) were introduced into the market only in the recent years, it is still considered new and has many concerns over its capability and efficiency. In this project, in collaboration with TUM CREATE, an attempt to develop an android application to display an estimation of the range of road distance that an EV would be able to travel with the amount of electric energy left in the vehicle. The android application would be made available on the tablet device installed in the EV. The Android application, Range Estimator is written in Java language for Android using Eclipse JUNO with necessary open-source libraries, such as Google Maps API, Mapsforge API and Graphhopper API. The Range Estimator is developed using two implementations with different libraries used and tests are carried out to measure each implementation’s performance. Finally, a choice will be made between the two implementations as the final implementation for the Range Estimator.