**5. Conclusions**

In this study, the battery behaviors under 13 different aging conditions are investigated experimentally, based on which, an aging-conscious battery model is proposed for energy management application. The optimal control strategy is then proposed for PHEVs energy management against the impact of battery aging. The presented control strategy can achieve the optimal control performance over the entire battery lifespan based on the PSO algorithm. The quantitative impact of battery aging on the energy consumption has been revealed, indicating that the capacity and internal resistance are the main factors that cause the extra energy cost. The presented energy management strategy is evaluated and analyzed by a simulation study under two typical driving cycles. The results indicate that the energy cost of PHEV can be increased by up to 15.19% due to the battery aging. The aging-conscious energy management can balance out some of the harmful effects that battery aging can have on energy efficiency. Compared with the strategy without considering the battery aging, the presented strategy can reduce the aging-induced energy consumption by up to 2.24% at certain driving condition.

**Author Contributions:** Conceptualization and methodology are provided by Z.C. and J.L.; software and data analysis are conducted by B.L.; validation is presented by N.Z. and S.L. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by "the National Natural Science Foundation of China, grant number 51977029, 51607030" and "the Fundamental Research Funds for the Central Universities, grant number N2003002".

**Conflicts of Interest:** The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
