LiFePO4 Battery Pack Research Articles

Analysis of Early-Stage Behavior and Multi-Parameter Early Warning Algorithm Research for Overcharge Thermal Runaway of Energy Storage LiFePO4 Battery Packs

Overcharging of lithium-ion batteries may lead to severe thermal runaway (TR) incidents, resulting in significant economic losses and safety hazards. Therefore, it is crucial to research early warning methods for TR behavior in overcharged lithium batteries. This study initially conducted overcharging experiments on LiFePO4 battery packs under different initial charging states and charging rates, analyzing variations in temperature, voltage, and inter-group pressure during overcharging. The TR process was divided into three stages: non-overcharged, early, and middle. Based on this, temperature change rate, pressure change rate, and voltage were extracted as input feature parameters, and the Mean Shift algorithm was employed for stage identification and classification of overcharging experiments on LiFePO4 battery packs. According to experimental results, the algorithm achieved an accuracy of over 96% in stage identification and classification of TR in overcharged lithium batteries, accurately determining the current stage of TR and providing a reliable and effective solution for preventing TR in overcharged lithium batteries.

Computational Modelling of Heat Transfer through Aluminium Metal Foams for LiFePO4 Battery Cooling

Abstract: Temperature is crucial for battery pack durability and power. Folded fin and serpentine channel cooling methods are mostly used to cool the pack. However, fluid absorption during cooling can reduce capacity and cause downstream temperatures to be higher than upstream. Consistent cooling is vital to prevent temperature variation and increase battery pack lifespan. This work is concerned with the computational study of heat dissipation from open-cell aluminium metal foam for cooling LiFePO4 battery packs. The battery module consists of six pieces of pouch cell and three pieces of the aluminium foam heat sink. In the present study, aluminium foams are positioned between the LiFePO4 battery modules that are arranged in a vertical manner. Thermal interaction between the battery module and aluminum foam was studied. The effect of pore density on heat dissipation performance at different mass flow rates was explored. It has been discovered that aluminium foam with suitable porosity and pore density can efficiently cool the LiFePO4 battery pack. This paper provides a theoretical framework for designing a thermal management system for lithium- ion batteries using aluminium foam. Background: Metal foam cooling is an established technique for thermal management of Lithiumion batteries in electric vehicles. Objective:: The present study aims to analyze heat transfer through aluminium metal foams for vertically aligned LiFePO4 battery pack cooling. Methods: The Darcy extended Forchheimer (DEF) model examines fluid flow through metallic foams, using the local thermal non-equilibrium model to determine heat transfer. Results: The impact of the density of pores in the aluminium foam on the average wall temperature and temperature difference along the battery surface is determined. The variation of heat transfer of lithium-ion battery modules for different mass flow rates is also studied. Conclusion: The results indicate that utilizing aluminium foam as a heat transfer medium for battery modules significantly enhances their thermal management performance.

Experimental investigation on the effects of natural convection on cylindrical LiFePO4 battery module for energy storage application

AbstractThe experiments with a LiFePO4 battery pack operating at room temperature and with various charge and discharge rates to analyze its durability are described in this study. At a temperature of 23°C with natural convection, the thermal performance of a cylindrical (LFP) battery is experimentally studied. In this study, the battery is fully charged. After reaching 14.6 V, the battery is charged at a current of 4.8 A for 10 min to allow for stabilization. The battery is then depleted at 4.8 A until its voltage hits 10.5 V, followed by an additional 10‐min resting time. The processes reached their highest and lowest temperatures, respectively, were 29°C and 22°C. The battery is charged for a total of 46.877 Ampere‐hours (Ah) during the course of the 10‐h operation at a constant current of 4.8 A. Similar to this, a 10‐h discharge operation is carried out with a constant current of 4.8 A, yielding a discharge of 47.207 Ah. The processes reached their highest and lowest temperatures, respectively, were 36°C and 24°C. Another possibility is to charge the battery at a steady 24 A until the voltage reaches 14.6 V, then let it rest for 10 min, a further 10‐min rest period is added after it is discharged at 24 A until its voltage hits 10.5 V. After 5 h of charging at 24 A, the capacity is 46.958 Ah, and after 5 h and 47.51 min of discharging at 24 A, the capacity is 47 Ah. The processes reached their highest and lowest temperatures, respectively, were 49°C and 33°C.

Effects of the cold plate with airfoil fins on the cooling performance enhancement of the prismatic LiFePO4 battery pack

To maintain the optimal battery performance, it is essential to develop an efficient battery thermal management system for keeping the battery operation temperature within the appropriate range. In this work, a novel design of cold plate featuring airfoil fin channel is developed as a highly effective cooling module of a prismatic LiFePO4 battery pack. The thermal performance of battery and the thermo-hydraulic performance of the cooling module for the cold plate featuring airfoil fin channel, U-type channel and serpentine channel are numerically investigated and compared to reveal the superiority of the novel cold plate. The results indicate that compared with the U-type channel and the serpentine channel, the airfoil fin channel can enhance the total heat dissipation amount by 3.47% and 4.64%, respectively. Besides, the airfoil fin channel can provide the smallest battery maximum temperature and temperature difference under the same coolant flow rate. The airfoil fin channel provides the smallest pressure loss and heat transfer coefficient but the largest overall thermo-hydraulic performance indictor in terms of j/f factor. Under the same requirement of battery cooling performance, the remarkably smaller power consumption is required for the airfoil fin channel compared with the U-type channel and serpentine channel.

Online State of Health Estimation for Series-Connected LiFePO₄ Battery Pack Based on Differential Voltage and Inconsistency Analysis

Low-complexity and accurate state of health estimation of series-connected batteries has always been a difficult problem to solve in a well-designed battery management system. Lithium iron phosphate battery has been widely used as energy storage carrier due to its better safety and longer cycle life. In this paper, we proposed an online state of health estimation method for lithium iron phosphate battery pack based on differential voltage and inconsistency analysis. According to the aging mechanism of lithium iron phosphate battery, the region capacity in differential voltage curve is extracted as health feature to establish an aging model. Furthermore, all four inconsistency cases that affect pack capacity are analyzed, and the calculation formulas are concluded relying only on three representative battery modules, thereby reducing the computational burden. The pack capacity is estimated to verify the feasibility of the proposed method at different aging cycles. The estimation errors of the state of health of eight in-pack battery modules are less than 2%, and further the maximum error for the battery pack is only 2.27% in all aging cycles. In addition, the maximum error of the state of health for the other battery pack is only slightly over 1% at different inconsistencies.

Thermal Management of a LiFEPO4 Battery Pack in a Cold Temperature Environment Using Phase Change Materials (PCMs)

Thermal Management of a LiFEPO4 Battery Pack in a Cold Temperature Environment Using Phase Change Materials (PCMs)

Combustion Gas Examination of a Battery Housing in Electrically Driven Heavy Goods Vehicle

Nowadays, electrically propelled vehicles are becoming more and more popular. Due to the propulsion system, the risks derived from the operation have changed, compared to the conventionally driven vehicles. The investigated vehicle has the same, new risk factor originating from the behaviour of rechargeable energy storage system (RESS) during combustion and there is only a minority of available literature dealing with the investigation of the battery housing. According to our assumption the housing is a fire comburent material that hinders the work of first responders. In this research we conducted the laboratory examination of a prismatic LiFePO4 battery cell and battery pack cover used in electrically driven vehicles during burning. Combustion gases were collected and were evaluated with the help of gas chromatography. Our results show that plastic housing and cell covers are not recommended in automotive industrial use, because of their comburent characteristics, also the combustion gases are severely harmful. This paper includes the method of sampling, the experiment itself and the results.

Revealing suppression effects of injection location and dose of liquid nitrogen on thermal runaway in lithium iron phosphate battery packs

Thermal runaway (TR) and TR propagation in lithium-ion batteries (LIBs) impose a fire risk. Despite liquid nitrogen (LN) can effectively suppress TR in small-capacity 18,650-type LIBs, its effectiveness in inhibiting TR and TR propagation among large-capacity LiFePO4 batteries requires further investigation. This study explores the two-way domino effect of TR and analyzes the distribution of energy flow. Furthermore, LN is applied to control TR propagation in large-capacity LiFePO4 battery packs, considering different LN injection doses and locations. The results demonstrate that injecting 11–18 kg of LN from above the battery pack effectively suppressed TR and its propagation. Injecting 18 kg of LN absorbs approximately 1.45 times more heat from the pack compared to injecting 11 kg of LN. Identifying high-risk LIBs and selecting appropriate LN injection locations are crucial. LN injection from the top of the pack successfully prevents TR propagation and absorbs 694.7 kJ of heat from battery 1#-4# at higher TR risk. However, TR propagates when LN is injected from the left or back side. The heat absorbed by LN from battery 1#-4# is 228.4 kJ and 447.9 kJ, respectively. This work is expected to guide suppressing TR and TR propagation of LIBs.

Optimal battery thermal management for electric vehicles with battery degradation minimization

The control of a battery thermal management system (BTMS) is essential for the thermal safety, energy efficiency, and durability of electric vehicles (EVs) in hot weather. To address the battery cooling optimization problem, this paper utilizes dynamic programming (DP) to develop an online rule-based control strategy. Firstly, an electrical–thermal-aging model of the LiFePO4 battery pack is established. A control-oriented onboard BTMS model is proposed and verified under different speed profiles and temperatures. Then in the DP framework, a cost function consisting of battery aging cost and cooling-induced electricity cost is minimized to obtain the optimal compressor power. By exacting three rules ”fast cooling, slow cooling, and temperature-maintaining” from the DP result, a near-optimal rule-based cooling strategy, which uses as much regenerative energy as possible to cool the battery pack, is proposed for online execution. Simulation results show that the proposed online strategy can dramatically improve the driving economy and reduce battery degradation under diverse operation conditions, achieving less than a 2.18% difference in battery loss compared to the offline DP. Recommendations regarding battery cooling under different real-world cases are finally provided.

Equalization method of ‘LiCoxNiyMn1-x-yO2 - LiFePO4’ hybrid battery pack based on charging electric quantity estimation

Battery packs are typically composed of identical cells arranged in series-parallel arrangements, such as LiCoxNiyMn1-x-yO2 battery packs or LiFePO4 battery packs. To fully leverage the advantages of both LiCoxNiyMn1-x-yO2 cells and LiFePO4 cells, manufacturers have proposed an innovative scheme where the two types of cells are connected in series to form a hybrid battery pack. However, the electrical characteristics of the two cells differ significantly. As capacity degradation and self-discharge, the electrical quantity difference between the cells and the configuration of the hybrid battery pack will gradually change. Therefore, a dissipative cell equalization algorithm for the hybrid battery pack based on charging electric quantity estimation is proposed in this paper. The objective of the algorithm is to stabilize the energy output of the hybrid battery pack. We implement the proposed algorithm in simulations, containing a hybrid battery pack model. Dissipation cell equalization algorithm based on charging electric quantity estimation is proved to be effective by comparing the cell electric quantity difference with/without the algorithm. The relationship between cells in the pack with the visualization of equalization is further analyzed. Results demonstrate that closely match the theoretical values achieved through the dissipative equalization strategy after approximately 15 to 20 standard cycles, with a relative difference of no more than 1 % and minimal fluctuations. Therefore, the equalization method can change and recover the electric quantity difference, and achieve the energy stabilization strategy of the hybrid battery pack.

Flexible phase change material packages for green transportation vehicles

Green transportation with net-zero CO2 emissions can only be possible with electric cars that possess reliable long-life batteries. Current hybrid/electric vehicles come with Li-ion batteries that must be kept within certain temperature limits for their safe and economic operation. At higher ambient temperatures, thermal run-aways lead to battery fire risks. Operation temperatures can only be attained by incorporating a cost-effective battery thermal management (BTM) system. This work studies a new, versatile, and high-capacity phase change material (PCM) package for BTM. LiFePO4 battery packs have been tested for different ambient temperatures in typical urban battery charge/discharge cycles. Our findings indicate that such packs with flexible PCM packages operate efficiently. We succeeded in keeping the maximum operation temperatures about 10–15 °C below that of reference battery packs without PCMs. Our economic and environmental assessments conclude that they will become an indispensable smart and clean pathway for real passive BTMs. Flexible PCM packages present a promising alternative to current BTM applications. The energy savings that are achieved with 30% prolonged battery life can decrease CO2 emissions by 1215–1755 kg CO2 depending on the reference fuel for one medium sized vehicle. Green transportation is no longer a myth.

Experimental Investigation of Thermal Runaway Behavior and Hazards of a 1440 Ah LiFePO4 Battery Pack

The thermal runaway (TR) behavior and combustion hazards of lithium-ion battery (LIB) packs directly determine the implementation of firefighting and flame-retardants in energy storage systems. This work studied the TR propagation process and dangers of large-scale LIB packs by experimental methods. The LIB pack consisted of twenty-four 60 Ah (192 Wh) LIBs with LiFePO4 (LFP) as the cathode material. Flame performance, temperature, smoke production, heat release rate (HRR), and mass loss were analyzed during the experiment. The results indicated that TR propagation of the LIB pack developed from the outside to the inside and from the middle to both sides. The development process could be divided into five stages corresponding to the combustion HRR peaks. In the initial stages, the main factor causing LFP battery TR under heating conditions was the external heat source. With the propagation of TR, heat conduction between batteries became the main factor. Hazard analysis found that the HRRmax of the LIB pack was 314 KW, more than eight times that of a single 60 Ah battery under heating conditions. The LIB pack had higher normalized mass loss and normalized THR (6.94 g/Ah and 187 KJ/Ah, respectively) than a single LFP battery. This study provides a reference for developing strategies to address TR propagation or firefighting in energy storage systems.

Quantitative diagnosis of the soft short circuit for LiFePO4 battery packs between voltage plateaus

An accurate diagnostic method on the soft short circuit (SSC) for the Li-ion batteries before it evolves to a critical safety issue is recognized as one of the most important functions in battery management systems. Because the SOC (state of charge)-OCV (open circuit voltage) curve of Lithium Iron Phosphate (LiFePO4 or LFP) batteries is flat, there are few diagnostic algorithms that focus on LFP. Therefore, this paper proposes a quantitative SSC diagnosis method for LFP battery packs within a narrow voltage window. The proposed method firstly find the median voltage between the two voltage plateaus during the constant current charging for all the cells in the battery pack. It takes the cell with the highest voltage as the reference cell, and calculates the time differences and electric quantity differences (EQDs) when the other batteries reach the median voltage during every charge. The leakage current and SSC resistance of the SSC cell can be calculated from the increase in EQD after each charge. A series of experiments with external resistors show that this method can identify the SSC resistances of 510 Ω and is suitable for various applications, especially when they are seldom fully charged or discharged.

Design and Implementation of DC Fast Charging for 48V LiFePO4 Battery Pack

This research focuses on developing a fast charging system to charge lithium-ion battery packs with a voltage rating of 48 volts. Standard battery charging uses a 0.25 C charging rate, which takes about 4 hours. The charging method in this study uses the constant current, constant voltage (CC-CV) method by adjusting the charging current at a charging rate of 1C, 2C, and 3C from the battery capacity. The buck converter determined the charging current value, setting it to produce a voltage of 53 V and a charging current of 10 A for a 1C charging rate, 20 A for a 2C charging rate, and 30 A for a 3C charging rate. Based on the testing, the battery charging time to reach 80% takes 57 minutes for charging rate 1C, 30 minutes for charging rate 2C, and 26 minutes for charging rate 3C.

Numerical Simulations for Indirect and Direct Cooling of 54 V LiFePO4 Battery Pack

In this study, three-dimensional thermal simulations for a 54 V Lithium-ion battery pack composed of 18 LiFePO4 pouch battery cells connected in series were conducted using a multi-scale electrochemical-thermal-fluid model. An equivalent circuit model (ECM) is used as a subscale electrochemical model at each cell node of the battery, which is then combined with the macro-scale thermal and fluid equations to construct a model of the battery and battery pack. With the model, the cooling effects of indirect cooling and direct cooling battery thermal management systems (BTMS) on the battery pack under rapid discharging conditions are explored. It is found that when the battery pack is discharged at 2C, indirect cooling of the bottom plate can effectively dissipate heat and control the temperature of the battery pack. Under the 10C discharging condition, the maximum temperature of the battery pack will exceed 100 °C, and the temperature uniformity will be very poor when using indirect cooling of the bottom plate for the battery pack. Direct air cooling is also unable to meet the cooling requirements of the battery pack at a 10C discharging rate. The possible reason is that the convective heat transfer coefficient of direct air cooling is small, which makes it difficult to meet the heat dissipation requirements at the 10C condition. When single-phase direct cooling with fluorinated liquid is used, the maximum temperature of the battery pack under the 10C discharging condition can be controlled at about 65 °C. Compared with air direct cooling, the pressure drop of fluorinated liquid single-phase direct cooling is smaller, and the obtained battery pack temperature uniformity is better. From the detailed study of fluorinated liquid single-phase direct cooling, it is concluded that increasing the coolant flow rate and reducing the cell spacing in the battery pack can achieve a better cooling effect. Finally, a new cooling method, two-phase immersion cooling, is investigated for cooling the battery pack. The maximum temperature of the battery pack discharged at a 10C rate can be controlled below 35 °C, and good temperature uniformity of the battery pack is also achieved at the same time. This study focuses on fluorinated liquid immersion cooling using numerical simulations, showing that it is a promising cooling method for lithium-ion battery packs and deserves further study. This paper will provide a reference for the design and selection of BTMS for electric vehicles.

A novel capacity and initial discharge electric quantity estimation method for LiFePO4 battery pack based on OCV curve partial reconstruction

LiFePO4 batteries are widely used in electric vehicles (EVs) and battery energy storage systems (BESSs). However, the consistencies in capacity, internal resistance, and open circuit voltage (OCV) limit the battery pack performance, which makes it difficult to evaluate the state information of the cells effectively without disassembling the pack. Therefore, this paper proposes a battery capacity and initial discharge electric quantity (DEQ) estimation method for series-connected battery packs based on partial reconstruction of the OCV curve. The aging characteristics of each cell are extracted based on incremental capacity analysis (ICA), which is taken as the transformation law for the OCV curve considering aging. And then the multipopulation genetic algorithm (MPGA) is utilized to optimize the transformation coefficients and obtain the reconstructed OCV curve of each cell in the pack. Finally, the actual capacity and initial DEQ of batteries at a low current rate are estimated according to the reconstructed complete OCV curve and optimized OCV curve transformation coefficients. The experimental results show that the estimation error of capacity is less than 5%, and the maximum estimation error of the initial DEQ is 5.56%.

Predictive Management Algorithm for Controlling PV-Battery Off-Grid Energy System.

This paper introduces an energy management strategy for an off-grid hybrid energy system. The hybrid system consists of a photovoltaic (PV) module, a LiFePO4 battery pack coupled with a Battery Management System (BMS), a hybrid solar inverter, and a load management control unit. A Long Short-Term Memory network (LSTM)-based forecasting strategy is implemented to predict the available PV and battery power. The learning data are extracted from an African country with a tropical climate, which is very suitable for PV power applications. Using LSTM as a prediction method significantly increases the efficiency of the forecasting. The main objective of the proposed strategy is to control the different loads according to the forecasted energy availability of the system and the forecasted battery state of charge (SOC). The proposed management algorithm and the system are tested using Matlab/Simulink software. A comparative study demonstrates that the reduction in the energy deficit of the system is approximately 53% compared to the system without load management. In addition to this, the reliability of the system is improved as the loss of power supply probability (LPSP) decreases from 5% to 3%.

Simulation Methods Development for an EV Battery Pack in Terms of Thermal and Safety Aspects

This paper is the representation of our effort at modelling a LiFePO4 battery pack for an electric vehicle (EV) and further carrying out simulations on it. The process involves creating a single cell and then making a combination of these cells to form a battery pack. The simulations assist us in monitoring the thermal behaviour of the 60Ah battery pack after working for a stipulated amount of time at 1 and 2 C rates. It can be observed that the battery pack may experience thermal shock or thermal runaway leading to the failure of battery pack. Hence it is of paramount importance that we keep a check on the temperature range of the battery. The pack functions best when its temperature is maintained in the range of 288K-308K. This is a challenge in the absence of cooling. Hence, we used air and PCM (RT15 & RT31) as coolants to accomplish the objective of maintaining the temperature of battery pack within the optimum range.

Analysis of the Charging and Discharging Process of LiFePO4 Battery Pack

A serious issue relative to the construction of electronic devices is proper power source selection. This problem is of particular importance when we are dealing with portable devices operating in varying environmental conditions, such as military equipment. A serious problem in the construction of electronic devices is the correct selection of the power source. In these types of devices, lithium-ion batteries are commonly used nowadays, and in particular their variety—lithium iron phosphate battery—LiFePO4. Apart from the many advantages of this type of battery offers, such as high power and energy density, a high number of charge and discharge cycles, and low self-discharge. They also have a major drawback—a risk of damage due to excessive discharge or overcharge. This article studies the process of charging and discharging a battery pack composed of cells with different initial charge levels. An attempt was made to determine the risk of damage to the cells relative to the differences in the initial charge level of the battery pack cells. It was verified, whether the successive charging and discharging cycles reduce or increase the differences in the amount of energy stored in individual cells of the pack.

Optimization of air-cooling technology for LiFePO4 battery pack based on deep learning

The forced air-cooling system is applied extensively in the battery thermal management system (BTMS) to ensure temperature uniformity because of the simple structure and low cost. In this paper, a BTMS of LiFePO4 cuboid battery module with adding different additional airflow outputs in typical U-type cooling system is designed to optimize temperature uniformity. Because the features of these additional airflow outputs, including positions, numbers and areas of them, influence the temperature of battery pack simultaneously, a nine-layer fully connected deep network AI model is built to find the relationship between temperature of pack and these features of additional airflow outputs in BTMS. The temperatures of batteries with different additional airflow outputs are simulated by a three-dimensional computational fluid dynamics (CFD) model. Comparing with the CFD simulation results, the AI model's mean absolute errors of maximum temperature and temperature differences are 0.046% and 0.99%, respectively. An optimal BTMS air-cooling design is found as a U-type structure adding three 4 mm additional airflow outputs with gaps of 40 mm, 120 mm, 10 mm, and 48 mm after comparison of 765,846 BTMS structures. The maximum temperature is decreased by 6.22 K, while the temperature difference is reduced by 40.36% compared to original design.