**4. Conclusions**

Based on LDM, this study characterizes all three types of polarization voltage of Lithium ion batteries under operating conditions. Three model parameters were used: dimensionless charge exchange current *J*0, ohmic resistance *Rohm*, and diffusion time constant *τ* to characterize activation polarization, ohmic polarization, and concentration polarization, respectively. A joint algorithm consisting of the PSO algorithm and the L-M method was used to identify the model parameters. The deviation of the model output terminal voltage from the actual terminal voltage was used as the accuracy criterion, and the proposed algorithm was compared with the PSO algorithm alone and the L-M method alone. In terms of the intercepted battery testing data, RMSE as the criterion, the voltage error of the joint algorithm was reduced 77.1% compared to the PSO algorithm only, and 72.3% compared to the L-M method only. To further test the effectiveness of the model and the identification algorithm, the identified model parameters were substituted into the second battery test data. It can be concluded that (1) the proposed scheme describes the nonlinear characteristics of the battery cell under the excitation of high dynamic driving conditions, (2) the model reflects the real physical-chemical processes inside the battery to a certain extent. To test the real-time performance of the proposed method, a hardware implementation platform for the real-time quantitative characterization of the polarization voltage of lithium-ion batteries was built, and the model parameters were calibrated and fitted using an offline method. The hardware platform was capable of realizing the basic function of quantitative polarization voltage characterization, and the update frequency of relevant parameters was 1 Hz, with good real-time performance. It has the potential for further development for BMS applications.

**Author Contributions:** B.X. and B.Y. proposed the novel method of polarization voltage characterization for lithium-ion batteries; B.Y. designed the experiment scheme and conducted experiments. B.Y. and J.C. designed and implemented the hardware platform; B.Y. wrote the paper. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by National Natural Science Foundation of China (Grant No. 51877120).

**Conflicts of Interest:** The authors declare no conflict of interest.

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