Analysis of NARXNN for State of Charge Estimation for Li-ion Batteries on various Drive Cycles

12/19/2020
by   Aniruddh Herle, et al.
9

Electric Vehicles (EVs) are rapidly increasing in popularity as they are environment friendly. Lithium Ion batteries are at the heart of EV technology and contribute to most of the weight and cost of an EV. State of Charge (SOC) is a very important metric which helps to predict the range of an EV. There is a need to accurately estimate available battery capacity in a battery pack such that the available range in a vehicle can be determined. There are various techniques available to estimate SOC. In this paper, a data driven approach is selected and a Nonlinear Autoregressive Network with Exogenous Inputs Neural Network (NARXNN) is explored to accurately estimate SOC. NARXNN has been shown to be superior to conventional Machine Learning techniques available in the literature. The NARXNN model is developed and tested on various EV Drive Cycles like LA92, US06, UDDS and HWFET to test its performance on real world scenarios. The model is shown to outperform conventional statistical machine learning methods and achieve a Mean Squared Error (MSE) in the 1e-5 range.

READ FULL TEXT

Authors

page 1

page 2

page 3

page 4

11/19/2020

A Temporal Convolution Network Approach to State-of-Charge Estimation in Li-ion Batteries

Electric Vehicle (EV) fleets have dramatically expanded over the past se...
02/01/2021

Machine learning pipeline for battery state of health estimation

Lithium-ion batteries are ubiquitous in modern day applications ranging ...
09/20/2020

State-of-Charge Estimation of a Li-Ion Battery using Deep Forward Neural Networks

This article presents two Deep Forward Networks with two and four hidden...
02/15/2022

Deep Convolutional Autoencoder for Assessment of Anomalies in Multi-stream Sensor Data

A fully convolutional autoencoder is developed for the detection of anom...
03/16/2020

Data Set Description: Identifying the Physics Behind an Electric Motor – Data-Driven Learning of the Electrical Behavior (Part I)

Two of the most important aspects of electric vehicles are their efficie...
12/07/2020

Space-Filling Subset Selection for an Electric Battery Model

Dynamic models of the battery performance are an essential tool througho...
09/10/2021

Range, Endurance, and Optimal Speed Estimates for Multicopters

Multicopters are among the most versatile mobile robots. Their applicati...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.