The accurate estimation of the state of charge, the state of health and the prediction of remaining useful life of lithium–ion batteries is an important component of battery management. It is of great significance to prolong battery life and ensure the reliability of the battery system. Many researchers have completed a large amount of work on battery state evaluation and RUL prediction methods and proposed a variety of methods. This paper first introduces the definition of the SOC, the SOH and the existing estimation methods. Then, the definition of RUL is introduced, and the main methods are classified and compared. Finally, the challenges of lithium–ion battery state estimation and RUL prediction are summarized, and the direction for future development is proposed.

The state of health and remaining useful life of lithium-ion batteries are important indicators to ensure the reliable operation of these batteries. However, because they cannot be directly measured and are affected by many factors, they are difficult to predict. This paper presents method of jointly predicting state of health and RUL based on the long short-term memory neural network and Gaussian process regression. This method extracts the batteries’ health factors from the charging curve, selects health factors with more relevance than the setting standard as the characteristic of capacity by the maximum information coefficient method, and establishes the battery aging and remaining useful life prediction models with Gaussian process regression. On this basis, the long short-term memory neural network is used to predict the trend of the change in health factors with the increase in cycles, and the results are input into a Gaussian process regression aging model to predict the state of health. Taking the health factors and state of health as the characteristics of remaining useful battery life, a battery remaining useful life model based on Gaussian process regression is established, and the change trend in the remaining useful life can be obtained by inputting the predicted health factors and state of health. In this study, four battery data sets with different depths of charge were used to verify the accuracy and adaptability of the algorithm. The results show that the proposed algorithm has high accuracy and reliability.

All-solid-state batteries have attracted wide attention for high-performance and safe batteries. The combination of solid electrolytes and lithium metal anodes makes high-energy batteries practical for next-generation high-performance devices. However, when a solid electrolyte replaces the liquid electrolyte, many different interface/interphase issues have arisen from the contact with electrodes. Poor wettability and unstable chemical/electrochemical reaction at the interfaces with lithium metal anodes will lead to poor lithium diffusion kinetics and combustion of fresh lithium and active materials in the electrolyte. Element cross-diffusion and charge layer formation at the interfaces with cathodes also impede the lithium ionic conductivity and increase the charge transfer resistance. The abovementioned interface issues hinder the electrochemical performance of all-solid-state lithium metal batteries. This review demonstrates the formation and mechanism of these interface issues between solid electrolytes and anodes/cathodes. Aiming to address the problems, we review and propose modification strategies to weaken interface resistance and improve the electrochemical performance of all-solid-state lithium metal batteries.

The installed capacity of energy storage in China has increased dramatically due to the national power system reform and the integration of large scale renewable energy with other sources. To support the construction of large-scale energy bases and optimizes the performance of thermal power plants, the research on the corporation mode between energy storage and thermal energy, including the optimization of energy-storage capacity and its operation in large-scale clean energy bases. In this paper, a large-scale clean energy base system is modeled with EBSILON and a capacity calculation method is established by minimizing the investment cost and energy storage capacity of the power system and constraints such as power balance, SOC, and power fluctuations. The research proposed a method of using coupled system of thermal energy storage systems primarily based on molten salt thermal storage and thermal power generation for rough modulation and using battery energy storage system for fine modulation tasks. Example of fine modulation includes frequency modulation and heating demand of the district, which significantly reduces the energy storage investment by more than 95%. A case study of a 10 MW clean energy base is conducted. The result shows that the overall pre-tax internal rate of return of the base project is 8%, which has good economic benefits.

Neutral-point voltage unbalancing is a common problem in three-level inverters. The original neutral-point voltage balancing circuit is the buck-boost converter. Since the inductor carries low frequency components, the power density is limited. At the same time, the efficiency is low because the soft switching cannot be realized. In this paper, a neutral-point voltage balance circuit based on resonant switched-capacitor converter (RSCC) is proposed. The proposed converter uses a series resonant inductor and resonant capacitor to transfer the unbalanced energy between two dc-link capacitors. Based on phase shift modulation, the RSCC circuit controls the output current to compensate the neutral-point current of the inverter to achieve the suppression of neutral-point voltage ripple. To achieve the minimum loss, a step-by-step optimal design is presented and the optimal switching frequency, resonant inductance and resonant capacitance can be derived. The proposed circuit has the advantages that all switches of RSCC can realize the zero voltage switching (ZVS), and the magnetic volume can be greatly reduced because only high frequency components flow through the inductor. A 400V-10A prototype of RSCC and the inverter is built, and main experimental results are provided to verify the time-domain analysis and the effectiveness of the proposed RSCC voltage balance circuit.