State of health estimation for Li-Ion battery using incremental capacity analysis and Gaussian process regression

By Xiaoyu Li, Changgui Yuan, Xiaohui Li, Zhenpo Wang. Energy, 2020

413 citations recorded by the source corpus.

Abstract The state of health for lithium battery is necessary to ensure the reliability and safety for battery energy storage system. Accurate prediction battery state of health plays an extremely important role in guaranteeing safety and minimizing maintenance costs. However, the complex physicochemical characteristics of battery degradation cannot be obtained directly. Here a novel Gaussian process regression model based on the partial incremental capacity curve is proposed. First, an advanced Gaussian filter method is applied to obtain the smoothing incremental capacity curves. The health indexes are then extracted from the partial incremental capacity curves as the input features of the proposed model. Additionally, the mean and the covariance function of the proposed method are applied to predict battery state of health and the model uncertainty, respectively. Four aging datasets from NASA data repository are employed for demonstrating the predictive capability and efficacy of the degradation model using the proposed method. Besides, different initial health conditions of the tested batteries are used to verify the robustness and reliability of the proposed method. Results show that the proposed method can provide accurate and robust state of health estimation.

Subfields: Automotive Engineering, Control and Systems Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/45a055c47ab107396a1c66d6857b4451ba1dfeae

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

1. Xianke Lin
2. Simona Onori
3. Xiaosong Hu
4. Yunhong Che

In Control and Systems Engineering

1. Xiaosong Hu
2. Yunhong Che
3. Simona Onori
4. Xianke Lin

In Electrical and Electronic Engineering

1. Xianke Lin
2. Simona Onori
3. Xiaosong Hu
4. Yunhong Che

Citations in the corpus

• Battery Health Prediction Using Fusion-Based Feature Selection and Machine Learning (2020, methodology): “By extending the multivariate Gaussian distribution to infinite dimension, the Gaussian process f (x) can be obtained, which is constructed by means of the mean function m(x) and the covariance function k(xi , x j) [90]”