| Popis: |
Growing usage of Electric Vehicle calls for the invention of new technologies to increase the effective utilization of the Electric Vehicle and battery technology. The battery is the soul of the electric vehicle, so proper utilization of the battery is very important. This project is decided to predict the Lifecycle of the Lithium Ion Battery with the help of Machine Learning Software. The aging of the battery will increase the operating costs, reduce the service life of the equipment, and affect the safe operation of the equipment. There is no ideal solution for the recycling of Li-ion batteries and it is not environmentally friendly. So, predicting the lifecycle of the battery plays a vital role. With the help of data driven linear regression process, the lifecycle is predicted in a shorter span of time than the conventional methods in practice. This is done with the help of Edge Impulse software which is a development platform for embedded machine learning. Predicting the lifecycle of a battery will be useful for battery manufacturers, people buying used batteries and to operators who own a large fleet of electric vehicles. By knowing the lifecycle of a battery, they can be effectively used for the required application. |
