Online Broadband Impedance Identification for Lithium-Ion Batteries Based on a Nonlinear Equivalent Circuit Model
, Luning Zhang 1,2, Rong Wang 3, Haifeng Dai 1,2 and Xuezhe Wei 1,2Round 1
Reviewer 1 Report
A well-written article with good English on an important subject aimed at improving battery diagnostics on the move. The method presented is thoroughly described, motivated and verified by experimental data. This article is of significant interest to peers however less so to a general audience.
Author Response
Point 1: A well-written article with good English on an important subject aimed at improving battery diagnostics on the move. The method presented is thoroughly described, motivated and verified by experimental data. This article is of significant interest to peers however less so to a general audience.
Response 1: Thank you very much for your valuable evaluation and recognition. WEVJ is a professional journal in the electric vehicle industry, so we hope to provide more specialized research and articles, which will inevitably increase the reading difficulty for non-professional readers. In the future, we will consider your suggestion and make the introduction section more attractive.
Reviewer 2 Report
Battery on-line parameter identification is important for SOH determination, health-conscious control, and smart energy managment strategy.
1) equivalent circuit models have been widely used in the battery state/paprameter estimation domain, the presented model in Figure 2 is the new contribution in this paper ? If not, please add the reference in the title of Figure 2.
2) the description of battery model should be rewritten. Please refer to the model description part in "Nonlinear extension of battery constrained predictive charging control with transmission of Jacobian matrix." International Journal of Electrical Power & Energy Systems 146 (2023): 108762.
3) the FFRLS depends greatly on its tuning process (several key parameters such as \lambda). Therefore, the tuning process should be robust against to different battery technologies (or in different operation conditions), how about the performance of your parameter identification method for different models/batteries/temperatures, and even different battery cells ?
Author Response
Point 1: equivalent circuit models have been widely used in the battery state/paprameter estimation domain, the presented model in Figure 2 is the new contribution in this paper ? If not, please add the reference in the title of Figure 2.
Response 1: Thank you for your criticism and correction. The model we have adopted is a first-order equivalent circuit model, which is widely used in the field of lithium-ion battery research and is not our contribution. We have added corresponding references to the article as required.
Point 2: the description of battery model should be rewritten. Please refer to the model description part in "Nonlinear extension of battery constrained predictive charging control with transmission of Jacobian matrix." International Journal of Electrical Power & Energy Systems 146 (2023): 108762.
Response 2: Thank you for your valuable suggestion. We have reviewed the references you provided. In the references you provided, the equivalent circuit model mainly describes the characteristics of the battery state over time, and as a linearized system, the state space expression is obtained after decoupling. However, in our research, we focused on the impedance characteristics of the battery, and the strong coupling of the internal state of the battery is also a very important part of our research, so we cannot decouple the current into the form you provided in the literature.
But after reading, we gained great inspiration and added the highlights from the literature you provided to the introduction section.
Point 3: the FFRLS depends greatly on its tuning process (several key parameters such as \lambda). Therefore, the tuning process should be robust against to different battery technologies (or in different operation conditions), how about the performance of your parameter identification method for different models/batteries/temperatures, and even different battery cells?
Response 3: Thank you for your valuable suggestion. On the one hand, in the experimental part of the paper, we conducted validation experiments targeting different factors such as temperature, initial SOC, and charge/discharge rate. The results showed that the identification methods we proposed had good results under different operating conditions; On the other hand, in the current common battery systems, although there are differences in battery materials, the basic reactions inside them are similar. Therefore, we believe that they can be described using the same equivalent circuit model. In terms of the applicability of different batteries, we have reviewed relevant literature and found that in one article, the author achieved accurate parameter identification of batteries in different aging states through the FFRLS algorithm. Therefore, we have reason to believe that our parameter identification method has good properties. We refer to the literature: "Remaining discharge energy estimation for lithium-ion batteries based on future load prediction considering temperature and aging effects." Energy 238 (2022): 121754.
