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The venting event of thermal runaway has attracted public attention due to safety issues aroused by frequent fire accidents of new energy vehicles. However, the quantitative description of venting behavior is incomplete for tests in a sealed chamber due to the initial violent injection. In this study, nine types of batteries covering 28 cases in total were employed to investigate the influence of energy density, ambient temperature, pressure, and SOC on the venting behavior, characterized by normalized gas amount; maximum gas releasing rate; and venting durations t50, t90, t95, and t99. Then, a ‘two-point’ fitting method was proposed to modify outcomes concerning real-time gas amounts. The results show that at 100% SOC, the normalized gas amount ranges within 0.075–0.105 mol/Ah for NCM batteries and 0.025–0.035 mol/L for LFP batteries, while the maximum gas releasing rate presents a strongly positive correlation with the capacity of NCM batteries (0.04–0.31 mol/s) and a slight increase for LFP batteries (0.02–0.06 mol/s). Eventually, the three venting patterns were summarized and advanced according to the energy density and SOC of the targeted battery. This research can provide a reference for risk evaluations of the venting process and safety design for structure and pressure relief in battery systems.

Renewable energy power generation systems such as photovoltaic and wind power have characteristics of intermittency and volatility, which can cause disturbances to the grid frequency. The battery system of electric vehicles (EVs) is a mobile energy storage system that can participate in bidirectional interaction with the power grid and support the frequency stability of the grid. Lithium iron phosphate (LiFePO4) battery systems, with their advantages of high safety and long cycle life, are widely used in EVs and participate in frequency regulation (FR) services. Accurate assessment of the state of charge (SOC) and remaining available energy (RAE) status in LiFePO4 batteries is crucial in formulating control strategies for battery systems. However, establishing an accurate voltage model for LiFePO4 batteries is challenging due to the hysteresis of open circuit voltage and internal temperature changes, making it difficult to accurately assess their SOC and RAE. To accurately evaluate the SOC and RAE of LiFePO4 batteries in dynamic FR working conditions, a thermal-electric-hysteresis coupled voltage model is built. Based on this model, closed-loop optimal SOC estimation is achieved using the extended Kalman filter algorithm to correct the initial value of SOC calculated by ampere-hour integration. Further, RAE is accurately estimated using a method based on future voltage prediction. The research results demonstrate that the thermal-electric-hysteresis coupling model exhibits high accuracy in simulating terminal voltage under a 48 h dynamic FR working condition, with a root mean square error (RMSE) of only 18.7 mV. The proposed state estimation strategy can accurately assess the state of LiFePO4 batteries in dynamic FR working conditions, with an RMSE of 1.73% for SOC estimation and 2.13% for RAE estimation. This research has the potential to be applied in battery management systems to achieve an accurate assessment of battery state and provide support for the efficient and reliable operation of battery systems.

Lithium batteries are being utilized more widely, increasing the focus on their thermal safety, which is primarily brought on by their thermal runaway. This paper’s focus is the energy storage power station’s 50 Ah lithium iron phosphate battery. An in situ eruption study was conducted in an inert environment, while a thermal runaway experiment was conducted utilizing sealed pressure containers and an external heating triggering mechanism. Both the amount of gas release and the battery’s maximum temperature were discovered. Using gas chromatography, the gas emission from the battery was examined. Its principal constituents included CO, H2, CO2, CH4, C2H4, and so on. Moreover, the experiment discovered a second eruption of lithium iron phosphate, and the stage of its eruption was separated by the pressure signal of the sealed experimental chamber, giving a theoretical foundation and technological backing for the thermal catastrophe safety of lithium batteries.

Electrochemical impedance spectroscopy (EIS) is a powerful tool for investigating electrochemical systems, such as lithium-ion batteries or fuel cells, given its high frequency resolution. The distribution of relaxation times (DRT) method offers a model-free approach for a deeper understanding of EIS data. However, in lithium-ion batteries, the differential capacity caused by diffusion processes is non-negligible and cannot be decomposed by the DRT method, which limits the applicability of the DRT method to lithium-ion batteries. In this study, a joint estimation method with Tikhonov regularization is proposed to estimate the differential capacity and the DRT simultaneously. Moreover, the equivalence of the differential capacity and the incremental capacity is proven. Different types of commercial lithium-ion batteries are tested to validate the joint estimation method and to verify the equivalence. The differential capacity is shown to be a promising approach to the evaluation of the state-of-health (SOH) of lithium-ion batteries based on its equivalence with the incremental capacity.

This paper proposes a total cost of ownership (TCO) model for battery sizing of plug-in hybrid electric vehicles (PHEVs). The proposed systematic TCO model innovatively integrates the Beijing driving database and optimal PHEV energy management strategies developed earlier. The TCO, including battery, fuel, electricity, and salvage costs, is calculated in yearly cash flows. The salvage cost, based on battery degradation model, is proposed for the first time. The results show that the optimal battery size for PHEVs in Beijing is 6–8 kWh. Several additional scenarios are also analyzed: (1) 10% increase in battery price or discount rate leads to an optimal battery size of 6 kWh, and 10% increase in fuel price shifts the optimal battery size to 8 kWh; (2) the longer and more dispersive daily range distribution in the U.S. increases the optimal battery size to 14 kWh; (3) the subsidy in China results in an optimal battery size of 13 kWh, while that in the U.S. results in 17 kWh, and a fuel savings rate based subsidy policy is innovatively proposed; (4) the optimal battery size with Li4Ti5O12 batteries is 2 kWh, but the TCO of Li4Ti5O12 batteries is higher than that of LiFePO4 batteries.

The lithium titanium oxide (LTO) anode is widely accepted as one of the best anodes for the future lithium ion batteries in electric vehicles (EVs), especially since its cycle life is very long. In this paper, three different commercial LTO cells from different manufacturers were studied in accelerated cycle life tests and their capacity fades were compared. The result indicates that under 55 °C, the LTO battery still shows a high capacity fade rate. The battery aging processes of all the commercial LTO cells clearly include two stages. Using the incremental capacity (IC) analysis, it could be judged that in the first stage, the battery capacity decreases mainly due to the loss of anode material and the degradation rate is lower. In the second stage, the battery capacity decreases much faster, mainly due to the degradation of the cathode material. The result is important for the state of health (SOH) estimation and remaining useful life (RUL) prediction of battery management system (BMS) for LTO batteries in EVs.

China and the US have become the world’s largest plug-in hybrid electric vehicle (PHEV) markets. Powertrain architecture is the framework of PHEV technology which represents its technical route. The research on the market development and technical route of Chinese and American PHEV is helpful to grasp the internal law of the global PHEV market and technology situation, and thus is significant to lay out a development strategy and technical route but has not been sufficiently studied. Therefore, an evaluation method of three dimensions combining market sales, powertrain architectures and performance indexes was proposed for comparative analysis, and PHEV mainstream architectures were put forward. Besides, qualitative evaluation levels from nine dimensions were built for architecture analysis, and fuel consumption to curb weight (FC2CW) as an indicator was introduced for economy evaluation. Some conclusions can be drawn: (a) The most mainstream architecture in sales volume is four-wheel drive (4WD) Bridge, and that in models’ amount is P2 in China, while those respectively are PS and P2 in the US. This reflects that a difference exists between the choice of the consumers and that of the automakers, and another difference also exists between the two countries. (b) With the phasing down of subsidies, the single-motor parallel architecture may become the first choice of China’s next technical route, while the 4WD Bridge will still be the main architecture for sports utility vehicles (SUVs) or sports car. (c) Among the models of the top five sales, the types and sales of SUVs in China are significantly more, however, the fuel economy rankings of theirs in the US are relatively better. (d) It is difficult to distinguish which architecture has the absolute best economy, but the fuel economy of the series type in the two markets is not very good.

Incremental capacity analysis (ICA) has been used pervasively to characterize the degradation mechanisms of the lithium-ion batteries, and several online state-of-health estimation algorithms are built based on ICA. However, the stairs and the noises in the discrete sampled voltage data obstruct the calculation of the capacity differentiation over voltage (dQ/dV), therefore we need methods to fit the sampled voltage first. In this paper, the support vector regression (SVR) algorithm is used to smooth the sampled voltage curve using Gaussian kernels. A parametric study has been conducted to show how to enhance the performances of the SVR algorithm, including (1) speeding up the algorithm by downsampling; (2) avoiding overfitting and under-fitting using proper standard deviation σ in the Gaussian kernel; (3) making precise capture of the characteristic peaks. A novel method using linear approximation has been proposed to help judge the accuracy of the SVR algorithm in tracking the ICA peaks. And advanced SVR algorithms using double σ and using cost function that directly regulates the differentiation result have been proposed. The advanced SVR algorithm can make accurate curve fitting for ICA with overall error less than 1% (maximum 3%) throughout cycle lives, for four kinds of commercial lithium-ion batteries with LiFePO4 and LiNixCoyMnzO2 cathodes, making it promising to be further applied in online SOH estimation algorithms.

Fuel cells are the most clean and efficient power source for vehicles. In particular, proton exchange membrane fuel cells (PEMFCs) are the most promising candidate for automobile applications due to their rapid start-up and low-temperature operation. Through extensive global research efforts in the latest decade, the performance of PEMFCs, including energy efficiency, volumetric and mass power density, and low temperature startup ability, have achieved significant breakthroughs. In 2014, fuel cell powered vehicles were introduced into the market by several prominent vehicle companies. However, the low durability and high cost of PEMFC systems are still the main obstacles for large-scale industrialization of this technology. The key materials and components used in PEMFCs greatly affect their durability and cost. In this review, the technical progress of key materials and components for PEMFCs has been summarized and critically discussed, including topics such as the membrane, catalyst layer, gas diffusion layer, and bipolar plate. The development of high-durability processing technologies is also introduced. Finally, this review is concluded with personal perspectives on the future research directions of this area.

The polymer electrolyte membrane (PEM) fuel cell system is considered to be an ideal alternative for the internal combustion engine, especially when used on a city bus. Hybrid buses with fuel cell systems and energy storage systems are now undergoing transit service demonstrations worldwide. A hybrid PEM fuel cell city bus with a hierarchical control system is studied in this paper. Firstly, the powertrain and hierarchical control structure is introduced. Secondly, the vehicle control strategy including start-stop strategy, energy management strategy, and fuel cell control strategy, including the hydrogen system and air system control strategies, are described in detail. Finally, the performance of the fuel cell was analyzed based on road test data. Results showed that the different subsystems were well-coordinated. Each component functioned in concert in order to ensure that both safety and speed requirements were satisfied. The output current of the fuel cell system changed slowly and the output voltage was limited to a certain range, thereby enhancing durability of the fuel cell. Furthermore, the economic performance was optimized by avoiding low load conditions.