Audible Battery Management System for Electric Vehicles
Liang He, CMTC Fellow


This project aims to transfer real-time battery information of electric vehicles into enjoyable audio signals, i.e., listen to the battery.

Problem that Inspired Research:
The operation of batteries need to be monitored, in real time, with a large number of physical quantifies such as voltage, discharge/charge current, temperature, remaining capacity, etc. Normal drivers may not have the knowledge to fully understand these information, especially when requiring real-time interpreting. 

Objective / Proposed Solution:
The proposed audible battery management system will convert these multi-modal battery information into audio signals, e.g., music, which drivers can interpret easily without causing distractions.

Greatest Challenge to Overcome:
The biggest challenge is to convert the battery into audio signals that are enjoyable and also informative. 

Benefits of Research:
This project will provide cross-discipline human-centered training opportunities to participating (under)graduate students. Also, this project covers the complete lifecycle of data science and engineering in data collection, preparation, analysis, management, and visualization, and thus prepares students for further data-oriented careers.

Real-World Application(s):
The automative industry and other commercial companies in battery-powered systems will benefit from this project.

Innovations to Media and Technology:
This project will open a new paradigm of “listen to the battery.”

Cutting-edge Technology Being Used:
We will use machine learning approaches to achieve the automatic mapping from battery information to enjoyable audio signals.

Transdisciplinary Collaboration:
This project integrates computer science, electric and mechanical engineering, and arts.