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In recent years, the burgeoning applications of hydrogen fuel cells have ignited a growing trend in their integration within the transportation sector, with a particular focus on their potential use in multi-rotor drones. The heightened mass-based energy density of fuel cells positions them as promising alternatives to current lithium battery-powered drones, especially as the demand for extended flight durations increases. This article undertakes a comprehensive exploration, comparing the performance of lithium batteries against air-cooled fuel cells, specifically within the context of multi-rotor drones with a 3.5kW power requirement. The study reveals that, for the specified power demand, air-cooled fuel cells outperform lithium batteries, establishing them as a more efficient solution.

The formation is a crucial step in the production process of lithium-ion batteries (LIBs), during which the solid electrolyte interphase (SEI) is formed on the surface of the anode particles to passivate the electrode. It determines the performance of the battery, including its capacity and lifetime. A meticulously designed formation protocol is essential to regulate and optimize the stability of the SEI, ultimately achieving the optimal performance of the battery. Current research on formation protocols in lithium-ion batteries primarily focuses on temperature, current, and voltage windows. However, there has been limited investigation into the influence of different initial pressures on the formation process, and the evolution of cell pressure during formation remains unclear. In this study, a pressure-assisted formation device for lithium-ion pouch cells is developed, equipped with pressure sensors.

Alternating current (AC) heating is an efficient and homogeneous manner to warm Lithium-ion batteries (LIBs) up. The integrated design of AC heating combined with the motor drive circuit has been studied by many scholars. However, the problems of excessive heating frequency (>1kHz) and zeros torque output of the motor during the heating process have not been solved. High-frequency AC excitation may be detrimental to the battery because the effect of high-frequency AC excitation on the state of health of the battery is unknown. In addition, although the zero-torque output can be realized by controlling the q-axis current to zero, the torque ripple is still difficult to eliminate in a real-world application. To further solve the above problems, the motor’s neutral conductor is pulled out and connected to a large capacitor to increase the current amplitude of the AC heating at low frequencies.

The application of Li(Ni0.8Co0.1Mn0.1)O2 (NCM811) cathode-based lithium-ion batteries (LIBs) has alleviated electric vehicle range anxiety. However, the subsequent thermal safety issues limit their market acceptance. A detailed analysis of the failure evolution process for large-format LIBs is necessary to address the thermal safety issue. In this study, prismatic cells with nominal capacities of 144Ah and 125Ah are used to investigate the thermal runaway (TR) characteristics triggered by lateral overheating. Additionally, TR characteristics under two states of charge (SoCs) (100% and 5%) are discussed. Two cells with 100% SoC exhibit similar characteristics, including high failure temperature, high inhomogeneity of temperature distribution, multi-points jet fire, and significant mass loss. Two cells with 5% SoC demonstrate only a slight rupture of the safety valve and the emission of white smoke.

Battery safety issues have severely limited the rapid development and popularization of electric vehicles. Harsh conditions such as high temperature accelerate the degradation of battery safety. To address this issue, a comprehensive analysis of the impact of high-temperature cyclic aging on lithium-ion battery safety is carried out. In the Accelerating Rate Calorimeter, lithium-ion batteries are performed on adiabatic thermal runaway tests and overcharge tests. Regardless of the fully-charged state or half-charged state, in the adiabatic thermal runaway process, high-temperature cyclic aging reduces the characteristic temperature, and the activation energy from the self-heating temperature to thermal runaway triggering temperature decreases. During the overcharge process, high-temperature cyclic aging increases the voltage plateau and the crest voltage before thermal runaway, and their corresponding charging temperature decreases.

Fuel cell electric vehicles (FCEVs) require multiple components to operate properly, and the fuel cell stack—the source of power—is one of the most important components. While the number of enterprises manufacturing and selling fuel cell stacks is increasing globaly year after year, the residual challenges of core components and technologies still need to be resolved in order to keep pace with the development of lithium-ion batteries (i.e., its primary competitor). Additionally, many production and distribution standards are seen as unsettled. These barriers make large-scale commercialization an issue. Use of Proton-exchange Membrane Fuel Cells in Ground Vehicles explores the opportunities and challenges within the PEMFC industry. With the help of expert contributors, a critical overview of fuel cells and the FCEV industry is presented, and core technology, applications, costs, and trends are analyzed.

With the degradation of lithium-ion batteries, the battery safety performance changes, which further influences the safe working window. In this paper, the pouch ternary lithium-ion battery whose rated capacity is 4.2 Ah is used as the research object to investigate the impact of the high-temperature calendar and cyclic aging on tolerance performance. The overcharge-to-thermal-runaway test is performed on the fresh cell and aged cell (90% SOH). The inflection point of voltage for aged cells appears earlier than that of the fresh cell, while the voltage corresponding to the inflection point is the same for them, which means that the voltage at which lithium plating occurs is the same. However, the voltage plateau and the crest voltage before thermal runaway of aged cell are significantly higher than that of the fresh cell. Besides, ohmic heat, reversible heat, and side reaction heat make contribution to the thermal runaway triggering.

High-nickel lithium-ion batteries extend the driving mileage of electric vehicles (EVs) to 600km without much cost increment. However, thermal accidents commonly occur due to their poor thermal stability, such as thermal runaway. To address the issue, a comprehensive analysis of the thermal runaway behavior of high-nickel lithium-ion batteries with different specifications is conducted. The thermal runaway process is divided into five stages based on self-heating generation, voltage drop, safety valve rupture, and thermal runaway triggering for the three tested cells. The three tested cells demonstrate similar behaviors during each stage of the thermal runaway process. However, there are still apparent differences between their characteristics. This study analyses the thermal runaway features from the following aspects: (i) characteristic temperature; (ii) the relationship between sudden voltage drop and characteristic temperatures; (iii) temperature recovery; (iv) thermodynamics.

Impedance is an important parameter of power lithium-ion batteries, which can represent battery characteristics and can also be used as an indicator for battery fault diagnosis. Since Electrochemical Impedance Spectroscopy (EIS) includes various electrode processes and information, it is more significant and worthwhile for lithium-ion batteries research. However, it is quite difficult to attain EIS online because of the nonlinear characteristics of batteries. Therefore, this paper focus on studying the nonlinear impedance characteristics of lithium-ion batteries and proposing a new method to calculate the EIS online based on Fast Fourier Transform (FFT). Data similarity analysis is used to study the influence of resting time, excitation current amplitude, bias current amplitude and the state of charge (SOC) on the impedance quantitatively.

Lithium-ion batteries (LIBs) with relatively high energy, power density and eco-friendly characteristic are considered as a vital energy source in consumer market of portable electronics and transportation sector especially in electric vehicles (EVs). To meet the higher capacity requirements, the nickel-rich LIBs with higher capacity has been used as the commercial power batteries. However, the battery with higher energy density is more destructive, which could result in thermal runaway accidents and make the battery safety issues become more and more prominent. Thermal runaway of LIBs is one of the key scientific problems in safety issues. Until now, the inducement of thermal runaway process is complicated which perplex researchers and industry a lot. On the one hand, the internal mechanism about thermal runaway should be deeply studied. On the other hand, in-situ monitoring should be developed to supply the mechanism study and early warning.

As the core component of electric vehicles (EVs), batteries attach increasingly general attention along with the rapid expansion of electric vehicle market. Battery performance effect directly the safety and reliability of the EVs, so its managing technologies are more and more crucial. Among them, the methods of estimating the state of health (SoH) and predicting remaining useful life become the focuses, which are essential to ensure their dependability and optimum performance over time. This paper mainly focuses on impedance modeling and aging research (aging diagnosis and life prediction) of lithium-ion batteries. Electrochemical impedance spectroscopy (EIS) technique is used to obtain impedance characteristic of batteries. On the one hand, equivalent circuit modeling (ECM) can be motivated by EIS, with the goal to fit measured impedance data using circuit elements.

When electric vehicle speeds up or slows down, rapidly changing current and voltage (di/dt and du/dt) would occurs in its lithium-ion power battery. In this way, the impedance of power battery would changes with parasitic parameters because that the ion transport in electrolytes would influence diffusion effect and polarization effect of battery. Thus, the lithium-ion battery cannot be regarded as ideal component in high frequency, which could cause unpredictable problem in electromagnetic interference (EMI). However, most previous studies took lithium-ion power batteries as disturbed objects or transmission routes, which ignore the electromagnetic interference of battery itself. Based on it, this paper analyses the internal mechanism of EMI in lithium-ion power battery, and simulates the distribution of electromagnetic field as well as it corresponding interference suppression measures. Firstly, the test platform for parameter extraction of battery cell is built.

State-of-Power (SoP) prediction of Li-ion battery is necessary in battery management system for electric vehicles in order to deal with limited conditions, prevent overcharge and over discharge situations, increase the life of the battery and provide effective battery operation. This article suggests a method to on-line predict the 10-s charge and discharge peak power of Li-ion battery by twice recursions. First with the dynamic battery model we use the first recursion based on a least square method to get parameters which are influenced by the state of charge of Li-ion battery and temperature, etc. The dynamic model is an equivalent circuit model. Current and voltage are input online into the battery model. By recursive least square method the parameters are updated in real time. Moreover, when we use a recursive method to get real-time parameters, we add an extra proper factor to abandon old datum, which increases the real-time capability of state-of-power prediction.

Regarding the lithium-ion batteries used in the electric vehicle, charging time and charging efficiency are the concern of the public. In this paper, a lot of experiments were conducted to investigate the common charging strategies, including the CC-CV (constant current-constant voltage) charging and the pulse current charging, for the LiFePO4 batteries, which are still widely used in commercial vehicles. Charging temperature and the charging current in the CC phase are the main influence factors to be studied for the CC-CV charging strategy, and the contribution of the CC phase and CV phase to the whole charging is analyzed from three aspects, including the time percent, charging energy efficiency and the capacity of battery at different temperatures and charging current.

Range anxiety problem has always been one of the biggest concern of consumers for pure electric vehicles. Accurate driving range prediction is based on accurate lithium-ion battery pack SOC (State of Charge) estimation. In this article, a complete SOC estimation algorithm is proposed from cell level to battery pack level. To begin with, the equivalent circuit model (ECM) is applied as the model of battery cell. ECM parameters are identified every 10% SOC interval through genetic algorithm. The dual extended Kalman filtering (DEKF) algorithm is adopted for cell-level SOC and ohmic resistance R0 estimation. The estimation accuracy of cell SOC and R0 is verified under NEDC dynamic working condition. The cell-level SOC estimation error is below 1%. However, cell inconsistency can always result in inaccurate cell SOC estimation inside the battery pack. The impact of initial SOC inconsistency and internal resistance inconsistency between cells on battery pack SOC is specifically analyzed.

With the rise of new energy vehicles, lithium-ion batteries have been widely used. However, the safety, cruising range and practicality of electric vehicles are still major obstacles to their development. Among them, the low-temperature performance of electric vehicles is receiving more and more attention. Lithium-ion batteries have poor low-temperature performance. At low temperatures, not only the charging efficiency is lowered, but also the energy that can be flushed is correspondingly reduced, thereby resulting in a decrease in capacity and an increase in aging. At present, the mechanism and influence factors of battery discharge aging have been studied relatively well, but there are few researches on low temperature charging aging of batteries.

For balancing Li-ion battery cells connected in series and effectively improving the consistency of the cells, a bi-directional equalization system based on fly-back transformer is proposed. Unlike the passive equalization technology using a resistor or active equalization with expensive DC-DC converter for the balancing among the cells, this equalization circuit consists of the fly-back transformer and RCD circuit, which can easily and cheaply realize the energy transfer between the whole battery module and the cells, and thus achieving bidirectional equalization. In this system, both the primary side and the secondary side of multi-winding transformer are connected to a MOSFET. All MOSFETs are controlled by the PWM signal. The control timing and duty ratio of the PWM control signal are determined through the simulation analysis. Meanwhile, an RCD circuit is applied at the primary side of multi-winding transformer for buffering the peak voltage caused by leakage inductance.

Lithium ion battery is considered as one of the most possible energy storage equipment for new energy vehicles (EV, HEV, etc.) because of the advantages of long cycle life, high power density and low self-discharge rate. However, under freezing condition high power battery suffers of significant performances losses. For example, they would suffer from significant power capability losses and poor rate performance, which would restrict the availability to delivery or to gain of high current in transient conditions. To evaluate those performance drawbacks and to make an efficient design, good mathematical models are required for system simulation especially for battery thermal management. In this paper, a three-dimensional homogenization thermal model of a 20 Ah prismatic lithium ion battery with LiFePO4 (LFP) cathode is described.

An alternating current (AC) heating method for a NMC lithium-ion battery with 8Ah capacity is proposed. The effects of excitation frequency, current amplitudes, and voltage limit condition on the temperature evolution are investigated experimentally. Current amplitudes are set to 24A(3C), 40(5C), and 64A(8C), and excitation frequencies are set to 300Hz, 100Hz, 30Hz, 10Hz, 5Hz, and 1Hz respectively. The voltage limitations are necessary to protect cells from overcharge and over-discharge. Therefore the voltage limit condition (4.2V/2.75V, 4.3V/2.65V, and 4.4V/2.55V) are also considered in depth to verify the feasibility of the AC heating method. The temperature rises prominently as the current increases, and the decrement of frequencies also lead to the obvious growth of battery temperature. The battery obtain the maximum temperature rise at 64A and 1Hz, which takes 1800s to heat up the battery from -25°C to 18°C.

Lithium-ion batteries have been applied in the new energy vehicles more and more widely. The inconsistency of battery cells imposes a lot of difficulties in parameter and state estimations. This paper proposes a new algorithm which can online identify the parameters of each individual battery cell accurately with limited increase of computational cost. An equivalent circuit battery model is founded and based on the RLS (recursive least squares) algorithm, an optimization algorithm with the construction of weight vectors is proposed which can identify the parameters of lithium battery pack considering inconsistency of single battery cell. Firstly, the average value of the parameters of the battery pack is identified with the traditional RLS algorithm. Then the ratios between the parameters of each battery cell can be deduced from the mathematical model of battery. These ratios are used to determine the weight vector of each parameter of individual battery cells.