Remaining useful life prediction is of great significance for battery safety and maintenance. The remaining useful life prediction method, based on a physical model, has wide applicability and high prediction accuracy, which is the research hotspot of the next generation battery life prediction method. In this study, the prediction methods of battery life were compared and analyzed, and the prediction methods based on the physical model were summarized. The prediction methods were classified according to their different characteristics including the electrochemical model, equivalent circuit model, and empirical model. By analyzing the emphasis of electrochemical process simplification, different electrochemical models were classified including the P2D model, SP model, and electrochemical fusion model. The equivalent circuit model was divided into the Rint model, Thevenin model, PNGV model, and RC model for the change of electronic components in the model. According to the different mathematical expressions of constructing the empirical model, it can be divided into the exponential model, polynomial model, exponential and polynomial mixed model, and capacity degradation model. Through the collocation of different filtering methods, the different efficiency of the models is described in detail. The research progress of various prediction methods as well as the changes and characteristics of traditional models were compared and analyzed, and the future development of battery life prediction methods was prospected.

Electric vehicles have a promising development prospect. As its core component, lithium-ion power battery plays a crucial role in different application scenarios. Aiming at the availability and safety of square ternary lithium batteries at different ambient temperatures and different current rates, charge-discharge cycle experiments are carried out to study the voltage, temperature and capacity changes of lithium batteries. The voltage plateau characteristics of lithium batteries under different working conditions are explored. The results show that when discharging at current rates of 0.1C, 0.25C, 0.5C, 0.75C, and 1C under the ambient temperature of −5 °C, 10 °C, 25 °C, and 40 °C, the terminal voltage of the battery changes smoothly during the voltage plateau period, the rise of the surface temperature has not reached the peak value, and the discharge capacity accounts for about 50%. The battery has better working performance. While at the ambient temperature of −20 °C, the discharge capacity accounts for the highest proportion in the stage from the open-circuit voltage to the initial voltage of the plateau period. The research results can provide a reference for the modeling and control strategy design of lithium-ion power batteries in the energy storage system of electric vehicles.

Lithium-ion power batteries, which are the foundation of electric cars and are expected to play a significant role in a variety of operating environments and application situations, have major development prospects. In order to obtain the optimal operation range of ternary Li-ion batteries under various current rates and test temperatures, the characteristics of the voltage plateau period (VPP) of batteries in different states are examined by piecewise fitting based on charging and discharging cycle experiments. The findings demonstrate that while charging at current rates of 0.10C, 0.25C, 0.50C, 0.75C, and 1.00C under temperatures of 40 °C, 25 °C, and 10 °C, the battery’s termination voltage changes seamlessly from 3.5–3.75 V, 3.55–3.8 V, 3.6–3.85 V, 3.7–4 V, and 3.85–4.05 V, the growth in surface temperature does not surpass its maximum level, and the charge capacity exceeds 50%. Batteries operate more effectively. When the test temperature is −20 °C, the voltage rebound stage that occurs in the initial period of charging at 0.50C, 0.75C, and 1.00C accounts for the highest charge capacity, close to 70%. The study’s findings can be used as a guide when designing a lithium-ion power battery’s model and control method for an electric vehicle’s energy storage system.

High power cylindrical Ni-MH battery cells have a heavy heat load because of their high discharge rate and large equivalent internal resistance. This heavy heat load, together with an imbalanced flow in parallel liquid cooling systems, can lead to variances in the temperature of each cell in the entire battery pack, thereby reducing the life cycle of the battery pack. In this paper, a parallel-series combined liquid cooling system for a 288V Ni-MH battery pack was designed, and several parameters that influence the flow balance of the system by heat transfer and fluid dynamics were calculated. Then, a thermal-fluid simulation was executed with different parameters using StarCCM+ software, and the simulation results were validated by a battery pack temperature experiment on a bench and in a vehicle. The results indicate that the cell’s temperature and temperature differences can be kept within an ideal range. We also determined that within the battery power requirements and structural spacing limits, the total flow rate of the cooling liquid, the cross-sectional area ratio of the main pipe to the branch pipes, and the number of internal supporting walls in each branch pipe need to be large enough to minimize the cell’s maximum temperature and temperature differences.

The hot-pressing process of the membrane electrode assembly (MEA) is one of the research hotspots in the field of the fuel cell. To obtain suitable titanium mesh-based MEA hot pressing process parameters, titanium mesh was used as electrode substrate material. The anode and cathode of MEA were prepared by the drip-coated method, and the titanium mesh-based MEA was prepared under different hot-pressing pressure and temperature, respectively. The performance of titanium mesh-based MEA was studied by morphological observation, elemental analysis, thickness measurement, single cell test and numerical fitting analysis. The results demonstrated that: with increasing hot-pressing pressure from 0 MPa to 10 MPa, the forming thickness of titanium mesh-based MEA is getting thin gradually, and the peak power density of titanium mesh-based MEA first increased and then gradually decreased; with increasing hot-pressing temperature from 115 °C to 155 °C, the peak power density of titanium mesh-based MEA enhanced at the beginning and then also gradually decreased. Under the premise of a hot-pressing time of 180 s and the optimal operating temperature of DMFC of 60 °C, the appropriate hot-pressing process conditions of titanium mesh-based MEA are a hot-pressing pressure of 5 MPa and a hot-pressing temperature of 135 °C. The results can provide a technological reference for the preparation of titanium mesh MEA for DMFC.

Battery electric vehicles (BEVs) are one of the most promising new energy models for industrialization and marketization at this stage, which is an important way to solve the current urban haze air pollution, high fuel cost and sustainable development of the automobile industry. This paper takes pure electric buses as the research object and relies on the operation information management platform of new energy buses in Nantong city to propose an electric bus cycle construction method based on the mixed interpolation method to process sparse data. Three different interpolation methods, linear interpolation, step interpolation and mixed interpolation, were used to preprocess the collected data. The principal component analysis method and K-means clustering algorithm were used to reduce and classify the eigen parameter matrix. According to the clustering results, different categories of moving section and idle section libraries were established. According to the length of time and the correlation among various types, several moving sections and idle sections were selected to form a representative driving cycle of Nantong city buses. The results show that the mixed interpolation method, based on linear interpolation and cubic spline interpolation, has a good processing effect. The average relative error between the synthesized working conditions and the measured data are 15.71%, and the relative error of the seven characteristic parameters is less than 10%, which meets the development requirements. In addition, the comparison and analysis with the characteristic parameters of the world typical cycle conditions (NEDC, WLTC) show that the constructed cycle conditions of Nantong city are reasonable and reliable to represent the driving conditions of pure electric buses in Nantong city, which can provide a reference for the optimization of the bus energy control strategy.