Fresh Batteries Research Articles

Insights into the Deterioration Mechanism of Charging Ability during Calendar Aging and Cycling Aging of High-Voltage Co-Poor NCM Cathode-Graphite Full Battery.

Lithium-ion battery (LIB) has gained significant recognition for the power cell market owing to its impressive energy density and appealing cost benefit. Among various cathodes, a high-voltage cobalt-poor lithium nickel manganese cobalt oxide cathode (Co-poor NCM cathode) has been considered as a promising strategy to enhance its energy density. Despite these advantages, high-voltage Co-poor NCM cathode-graphite full battery usually suffers from poor rate performance. However, fast charging has been a key indicator for widespread application of power batteries. Although many efforts have been made to improve the charging performance of fresh batteries, few works investigate the charging ability during calendar aging and cycling aging of high-voltage Co-poor NCM cathode-graphite full battery. In this work, we found that the charging ability becomes worse during calendar aging and cycling aging. Results showed that the increasing charge transfer resistance from the cathode is the major obstacle to achieving fast charging during the aging process. To address the problem, high-voltage Al2O3-coated Co-poor NCM cathode successfully prepared via a simple atomic layer deposition (ALD) method has been developed to reduce the decay of charging performance during calendar aging and cycling aging. Al2O3-coated NCM cathode can effectively reduce the growth rate of the resistance of cathode, which is benefiting from the conversion of Al2O3 into LiAlO2 with high ionic conductivity and the restriction formation of rock salt phase. Benefiting from the decreased charge transfer resistance of the NCM cathode, the mismatch of the lithium-ion reaction kinetics is well alleviated, thus effectively reducing the polarization under fast charging. As a result, Al2O3-coated NCM cathode-graphite full battery shows the slow deterioration of charging performance during the aging process. This work provides a promising strategy for constructing fast-charging batteries during calendar aging and cycling aging.

Reliability–flexibility integrated optimal sizing of second‐life battery energy storage systems in distribution networks

AbstractSecond‐life batteries (SLBs), which are batteries retired from electric vehicles (EVs), can be used as energy storage systems to enhance the performance of distribution networks. Two issues should be addressed particularly for the optimal sizing of SLBs. Compared with fresh batteries, the failure rate of SLBs is relatively high, and timely and preventive replacement is needed. In addition, the flexibility introduced by EVs and installed SLBs should be coordinated to achieve optimal economic benefits. This paper focuses on the efficient utilization of SLBs by highlighting reliability‐flexibility concerns in optimal sizing. The model is formulated as a bi‐level model. On the upper‐level, considering the operational reliability constraints of SLBs, decisions regarding the investment and replacement of SLBs are optimized. Distribution network operations are improved on the lowerlevel, with an effective spatiotemporal flexible dispatch strategy for EVs. Finally, a linearized process for the optimal sizing of SLBs is presented and efficiently implemented. The Sioux Falls network and IEEE 69‐node distribution network are coupled as the test system. According to the simulation results, when the state of health of the SLBs decreased to 70%, the conditions were unreliable. The differences in the optimal SLB size and costs considering reliability and flexibility are highlighted.

Study on the effect of low-temperature cycling on the thermal and gas production behaviors of Ni0.8Co0.1Al0.1/graphite lithium-ion batteries

With their high energy density and long cycle life, lithium-ion batteries (LIBs) are currently the most promising electrochemical energy storage system for electric vehicles. However, their safety and cycling performance can be significantly compromised in low-temperature environments due to lithium plating and other factors. Therefore, it is essential to study the safety of aging batteries. In this study, we focused on a commercially available high-specific-energy Ni0.8Co0.1Al0.1 cathode system battery and simulated the aging of the battery by long-term cycling at 0 ℃. This study compares and analyzes the samples on the basis of the previous ones in terms of heat production power, thermal runaway (TR) characteristics and gas production characteristics. It reveals the influence of low-temperature aging on the comprehensive performance of lithium batteries in a more comprehensive way. The results show that the charging pattern of all three characteristics is related to the aging degree of the battery. In terms of the thermal characteristics, the relative change in specific heat capacity of the aged battery is only between 0.32 % and 1.08 % compared to that of a fresh battery, so the effect of ageing on the specific heat capacity of the battery is negligible. The average heat generation power of batteries with different state of health (SOH) is not monotonically increasing with the decrease of SOH, the threshold of dramatic increase is SOH = 80 %. In terms of TR characteristics, the onset temperature of exothermic reactions (TOER) of aged batteries is significantly lower than that of fresh batteries. With the decrease of SOH, TOER also decreases gradually. Compared with batteries with different SOHs, the more seriously aged the battery safety valve opens earlier, and the TR occurs earlier. In terms of the TR gas production characteristics, the more severely aged the battery, the earlier the safety valve opens compared to a fresh battery. The most gas is produced when SOH = 70 %, which increases the risk of catastrophic damage.

Auction-based peer-to-peer energy trading considering echelon utilization of retired electric vehicle second-life batteries

Lately, the growing emergence of electric vehicles (EVs) brings problems of retired batteries proliferation. Seeking effective application scenarios targeting echelon utilization of retired EV second-life batteries (EVSLBs) becomes important. This paper proposes an auction-based P2P energy trading approach in a residential community market that incorporates retired EVSLBs utilization. A unified P2P energy trading model is proposed to coordinate the economic layer and the physical layer. In the economic layer, the household energy management system (HEMS) of each agent is in charge of operating and market bidding through optimization models to maximize their net profit. Comprehensive operation models of fresh batteries and retired EVSLBs have been proposed and embedded into HEMS models. The battery life degradation issue is also considered by calculating the cycling cost. The P2P energy trading is conducted by a double-sided auction method with an average pricing market (APM) mechanism, in which the re-bidding process is allowed. In the physical layer, voltage issues and line congestion management are considered. There is a community manager in the P2P market to ensure the economic layer decisions do not violate the constraints in the physical layer. The proposed models are tested on the modified IEEE 33-bus distribution system and the comparison between new batteries and retired EVSLBs in the community market is discussed based on the simulation results. The echelon utilization effectiveness of EVSLBs in residential P2P trading has been verified as well.

Battery Venting Caused By Fast Charging

Lithium-ion batteries (LIBs) experience high risks of failure during unreasonable fast charging. Various degradation mechanisms inside the LIBs such as lithium (Li) plating, solid electrolyte interphase growth and electrolyte dry-out can undermine the electrochemical performance and induce massive gas generation alongside the operation. As a typical failure behaviour, venting occurs when the internal pressure of battery cell exceeds the safety threshold, releasing the gaseous products as well as depressurizing the cell. Recent studies1–3 of thermal runaway (TR) tests after fast charging have found that accumulated plated Li can react with electrolyte at elevated external temperatures, decreasing both self-heating and onset temperatures of TR. Yet, how fast-charging degradation will affect battery venting behaviours remains unclear.To answer this question, in this study, a series of fast charging experiments under controlled cooling as well as adiabatic TR tests were conducted with 51 Ah LiNi0.6Mn0.2Co0.2O2/graphite prismatic LIBs. The results showed that the prismatic battery underwent severe Li plating with over 30% capacity fade after 10 cycles of 4C charging. In the adiabatic TR tests, the aged batteries after 4C charging exhibited lower self-heating temperature and venting temperature as compared to the fresh batteries, by 51 ℃ and 34.4 ℃ respectively. This can be explained by the additional gas generation from the reaction between plated Li and electrolyte in the fast-charged batteries. Gas analyses of 120 ℃ hot-box tests for the degraded anodes with the electrolyte showed that the vented gas at the early venting stage primarily consisted of carbon dioxide, carbon monoxide and ethylene. The same charging protocols were then conducted in a natural convection thermal chamber with poor heat dissipation, where the temperature rise was much higher than those under forced convection as expected. Excessive cycling operations with off-limit charge rates (5C and 5.6C) were observed to directly cause battery swelling and venting without TR, and the temperature decreasing rates during rest after each charging process tend to slow down and even remain stable during a certain period of time. This indicates that the exothermic reaction between plated Li and electrolyte can be directly triggered by fast charging if heat removal is not effective enough. The findings provide useful insights into battery venting induced by fast charging, which can shed light on battery safety evaluation for fast charging techniques.Acknowledgements:This work is supported by the Faraday Institution BESAFE project (FIRG038), the Imperial College President’s PhD Scholarship Scheme (funded by EPSRC), the National Natural Science Foundation of China (Grant No. 52207241), China National Postdoctoral Program for Innovative Talents (grant no. BX20220171), China Postdoctoral Science Foundation (grant no. 2022M711760), and Shuimu Tsinghua Scholar Program (grant no. 2021SM130).

Spent-graphite anode from failed batteries: Regeneration and chemical prelithiation for sustainable fresh Li-ion batteries

Recycling of spent lithium-ion batteries require substantial attention for a sustainable future. Increasing deployment of batteries leads to large volume of failed batteries few years later depending on life time of the batteries. Recycling of graphite from the failed batteries has been mostly ignored. Graphite requirement of 1800 kt by 2030 is projected, which is approximately 260 % increase compared to present consumption. Present work unveils a solution to the increasing demand of battery-grade graphite anodes by a sustainable process. The combined practice of regeneration and prelithiation of spent-graphite (SG) is a viable solution for industrial scale processing. Regeneration process includes two steps, washing with N-Methyl-2-pyrrolidone and thermal processing. Regenerated SG has been tested for half-cell that delivered a poor initial Coulombic efficiency (ICE) of about 65 % only, which could affect the full-cell performance. To improve ICE, a chemical prelithiation strategy leading to higher ICE with a mean value of 103.5 % has been achieved. Also, reversible capacity of about 410 mAh/g at a specific current of 100 mA/g, good cycling stability and rate capability has been demonstrated. Further, the prelithiated SG anode coupled with LiMn2O4 cathode delivered an initial energy density of 370 Wh/kg in a lab-scale cell demonstrating its potential.

Thermal runaway characteristics of NaCl salt solution-immersed 18650 batteries: Impacts of concentration and state of charge

Lithium-ion batteries are at risk of immersion in seawater during practical applications, presenting a substantial safety challenge. In this work, the thermal runaway characteristics and degree of corrosion of 18,650 lithium-ion batteries were examined at various NaCl concentrations and states of charge (SOCs). Results indicate that corrosion increases with both NaCl concentration and SOC. The onset time (tTR) and onset temperature (TTR) of thermal runaway decrease with increasing SOC. The TTR is considerably higher for batteries immersed in 5 % NaCl solution compared to batteries without immersion and immersed in 2.5 % NaCl solution, while the tTR demonstrates the opposite trend. The maximum temperature (Tmax) of thermal runaway initially increases and then decreases with increasing salt concentration for batteries with SOC >100 %, while it decreases as salt concentration increases for batteries with SOC <100 %. The mass loss of immersion increases with the increase in salt concentration and SOC. The mass loss and peak heat flux during thermal runaway of batteries immersed in salt solution are significantly lower than those of fresh batteries. These results will contribute to a better understanding of the thermal runaway risk of lithium-ion batteries with different SOCs following immersion in salt solution.

Can retired lithium-ion batteries be a game changer in fast charging stations?

As the global popularity of electric vehicles (EVs) continues to grow, the demand for EV batteries has significantly increased. Unfortunately, when the battery state of health (SoH) reaches a certain value, the batteries may no longer meet the driving requirements of EVs, resulting in many retired batteries. Properly disposing of these batteries is a major challenge. In this paper, we will take fast charging stations (FCSs) as an example to evaluate the economic feasibility of reusing retired batteries, which is one of the most environmentally friendly methods of disposal. To make a fair comparison between fresh and retired batteries, a bi-level sizing framework is designed to determine the optimal sizes of fresh and retired batteries, as well as photovoltaic (PV) panels in FCSs, to minimize the total cost. To ensure the high fidelity of results, diverse EV travel patterns are considered to generate the charging power demand. Additionally, a dynamic battery degradation model focused on batteries that have not yet reached their turning point is developed. This model is designed to precisely quantify the gradual reduction in battery capacity. We conducted several representative case studies using real-world data, and the simulation results indicate that FCSs with fresh batteries can achieve 42.2 % cost savings compared to those without energy storage systems, while retired batteries can achieve an additional 5.41 %–11.79 % cost savings under different scenarios. These findings can be generalized that retired batteries are promising in small-scale applications due to the relatively low refurbishment cost, and a new market stream can be potentially generated in this direction.

Study on the combustion behaviors and thermal stability of aging lithium-ion batteries with different states of charge at low pressure

Currently, there are many application scenarios for lithium-ion batteries (LIBs) in high-temperature environments, such as large-scale energy storage, electric vehicles, aviation and so on. However, the fire and explosion risks of LIBs will pose a serious threat to transportation, industry applications, and environment. In this work, hence, considering the influence of ambient pressure, a series of experiments are performed to study the characteristics of thermal runaway (TR) for commercial LIBs with different states of charge (SOCs). Relative to past research on fresh batteries, aging LIBs whether at 100 % SOC condition or at lower SOCs, did not particularly exhibit significant spark ejection. The simultaneous burning flame was vertically upwards and no petal-shaped flame appeared. And the maximum flame temperature of LIBs during TR are 394 °C, 368 °C, 469 °C and 508 °C from 30 % SOC to 100 % SOC, respectively. The maximum flame temperature and average mass loss rate of LIBs show a correlation with SOC. Given that the combustions of gases and most ejected combustibles are significantly affected by the environmental pressure, the modified energy balance equation of the battery during the entire TR process is established to quantitative the relationship between the cell surface temperature and SOC under different environmental conditions. These results will help to further identify the risk of the TR process of LIBs with different SOCs after high-temperature aging, and provide a scientific basis for the transportation and use of batteries.

Improving Aging Identifiability of Lithium-Ion Batteries Using Deep Reinforcement Learning

As lithium-ion batteries age, the lithium inventory and active materials are gradually lost, limiting their lifespan. The stoichiometric range, which refers to the operable range of the amount of lithium in the electrode, has been considered a representative and comprehensive indicator for predicting the aging process. For the efficient and safe use of lithium-ion batteries, the cathode and anode stoichiometric ranges should be identified as accurately as possible. Accordingly, because the identification accuracy depends on the input signals and system operating conditions, suitable input current profiles should be designed for various operating conditions to improve identifiability. This article proposes a deep reinforcement learning (DRL)-based identifiability improvement scheme to estimate the stoichiometric range of a lithium-ion battery more accurately. In particular, a well-known reinforcement learning scheme [i.e., twin-delayed deep deterministic policy gradient (TD3)] is employed with an inverted bottleneck network (IBN) identifier. The policy determines a suitable current input profile every second by considering previous voltage and current profiles. The simulation results show that the proposed scheme can provide an identifiability-improved current input profile, even under different initial state-of-charge (SOC) conditions. Experiments with fresh and aged batteries were conducted to validate the proposed scheme.

Benefit assessment of second-life electric vehicle lithium-ion batteries in distributed power grid applications

Lithium-ion batteries in electric vehicles (EVs) are typically replaced after they lose about 20% of their capacity. With the rapid growth in EVs, there will be a tremendous potential to re-use the remaining EV battery capacities in power systems. Hence, this work focuses on capturing the economic benefits of using such second-life (SL) EV batteries. While previous works mainly focus on bulk storage applications, we demonstrate that the most beneficial route for SL batteries lies in distributed applications in power systems. Specifically, refurbishment and grouping of SL battery packs pose technical and operational challenges, thereby incurring significant costs and risks when large battery packs are adopted in bulk applications.Instead, when distributed at the residential and micro-grid level, such refurbishment costs and operation risks can easily be avoided as only small-size battery packs are required. An experimentally-validated model is incorporated to capture the battery capacity degradation and used to compare fresh batteries and SL-batteries. Using a model predictive control scheme and a 33-bus power network, the benefits of SL-batteries are quantified and verified.

All Right. Good Night. (Excerpt)

All Right. Good Night. (Excerpt)

A Comparison of Simple Closed-Form Solutions for the EOQ Problem for Exponentially Deteriorating Items

Some inventory items deteriorate and lose their useful life while in storage due to evaporation, spoilage, pilferage, and chemical or mechanical breakdown. Some examples of this phenomenon are the inventories of fresh food, batteries, electronic items, and petroleum products (such as gasoline and turpentine). Economic and environmental sustainability requires minimizing deterioration losses in inventories throughout the supply chain while optimizing the ordering decisions. This is especially important for food items because, globally, about one third of the food that is produced for human consumption is wasted, causing economic, environmental, political, and societal problems. Food production consumes large amounts of resources such as land, freshwater, fossil fuels, and labor. The same is true for items such as petroleum and chemical products. Exponential deterioration is a commonly used approach to model this phenomenon, which results in an exponentially decreasing inventory level function. An important extension of the basic economic order quantity (EOQ) model is its application to exponentially deteriorating items. In the exponentially deteriorating items model, the rate of deterioration per unit time for the stocked items is proportional to the amount of available physical inventory at any given time. This results in an exponentially declining inventory level over time. This problem normally does not lend itself to a closed-form optimal solution due to the coexistence of polynomial and exponential terms; hence, approximations are used, but the existing approximations yield closed-form solutions that are far from intuitive. In this research, we develop new approximate closed-form solutions for the basic problem and its backordering extensions that are intuitive and very easy to interpret, as well as more accurate; therefore, they are very attractive to practitioners. We provide extensive experimental results to demonstrate superiority of our approximate closed-form solutions.

Optimal techno-economic feasibility study of net-zero carbon emission microgrid integrating second-life battery energy storage system

With the increasing adoption of variable renewable sources (VRE) and the deployment of electric vehicles (EVs) in the market, the share of harmful carbon emissions is reducing continuously. Forming a microgrid (MG) is the best way to integrate renewable energy sources (RES) to make a low-carbon path for electrification. Second-life batteries (SLBs), derived from the first-life application of batteries used in EVs, are lower in price as compared to fresh EV batteries and have sufficient remaining capacity as energy storage for MG applications. Therefore, to show the techno-economic feasibility of SLBs, this paper shows a comparative study of MG consisting of photovoltaic (PV)/floating PV/wind/biogas with fresh Li-ion batteries (LIBs) and SLBs. This paper analyses 4 hybrid models with fresh LIBs in off-grid and grid-connected mode, and based on HOMER-Pro an optimal model is finalized for the Asian Institute of Technology (AIT), Pathumthani, Thailand. From, six different cases of fresh LIBs, the optimal case is also selected by considering the lowest net present cost (NPC) and cost of energy (COE). With the significant amount of reduction in NPC and COE, the grid-connected hybrid models are found to be more economically viable than the off-grid models. The grid-connected optimal hybrid model is further analyzed with SLBs where a range of cost multipliers (CMs) and energy throughputs are considered as the sensitivity parameters for SLBs. The results obtained from HOMER-Pro show that the grid-connected optimal model with SLBs reduces the NPC and COE by 36% and 35%, respectively, compared to the fresh LIBs. Hence, the optimal system shows the lowest NPC and COE as, 4,136,254$ and 0.0411$/kWh, respectively, with the SLBs.

Online state of health monitoring of lithium-ion battery based on model error spectrum for electric vehicle applications

Lithium-ion battery, as the mainstream power source of electric vehicles, suffers the performance degradation in the long-term vehicular usage. Battery health monitoring is quite an important task of the battery management system. This paper presents a novel method of online estimating the battery state of health (SOH) based on the evolution of the model error during the battery aging process. The monitoring model is established by using the test data of fresh batteries. During the process of battery aging, the model precision gradually declines and there is an implicit correlation between the aging degree and the distribution of model error. The model error spectrum (MES) is established based on the kurtosis and skewness of the model error statistics. It is found that there is an exponential relation between battery SOH and the MES. Based on the above work, the online SOH estimation is proposed by obtaining the MES within the historical data in a pre-set time window. The experiments are used to evaluate the presented method. The results indicate that the precise estimation results of battery SOH can be obtained with the error less than 1.07%. It is expected that the presented method is useful in online health monitoring and prognosis applications of the lithium-ion batteries in electric vehicles.

Sorting and grouping optimization method for second-use batteries considering aging mechanism

With the wide application of lithium-ion batteries in electric vehicles(EVs) and battery energy storage systems(BESSs), numerous retired lithium-ion batteries have to face the problem of the disposal and reuse. However, the existing sorting method for fresh batteries takes the external characteristics such as battery capacity and internal resistance as the sorting characteristic index, which fail to guarantee high efficiency and long service life simultaneously in specific second-use application scenes. This paper proposes a novel sorting and grouping method for retired batteries considering both characteristic parameters including aging mechanism and application scenes. First, the multi-factors including capacity, internal resistance and Incremental Capacity Analysis (ICA) based aging mechanism indicator, are extracted from experiments. Second, a fuzzy clustering algorithm is utilized to sort retired batteries according to the requirement of two typical application scenes, energy storage and peak load shifting, which are characterized by high capacity and instantaneous high power charge/discharge, respectively. Finally, 80 retired LiFePO4 batteries are screened and grouped using the proposed method. The results show that the proposed sorting method can effectively select batteries considering aging mechanism to ensure good performance and consistency in both application scenes.

Flexible Integrated Network Planning Considering Echelon Utilization of Second Life of Used Electric Vehicle Batteries

The echelon utilization of retired batteries has attracted more attention as the market share of electric vehicles (EVs) increases steadily year by year. The current battery recycling methods cannot utilize the remaining value of these retired batteries effectively. Studies have shown that second-life batteries (SLBs) have a much lower cost compared to fresh batteries but retain a certain capacity simultaneously, which means that they have a high secondary utilization value. Therefore, this article proposes a novel multistage system planning model, including battery energy storage system (BESS). BESS designed in this article involves not only the use of fresh batteries but also the echelon utilization of SLBs and considers the multiple lifespan cycles based on its state of health (SOH). Moreover, the proposed planning strategy integrates the electricity and transportation networks in the first stage and evaluates the flexibility of the planning system by comparing the adaptation costs of each system in the second stage. The proposed planning model is verified on the IEEE 33-bus electricity system and the 20-node transportation system. According to the simulation results, the differences in system cost and system operation situations caused by fresh batteries and SLBs are analyzed, verifying the effectiveness and flexibility of echelon utilization of SLBs.

State-of-charge estimation tolerant of battery aging based on a physics-based model and an adaptive cubature Kalman filter

Battery performance declines with aging. This phenomenon makes it difficult to estimate the state-of-charge (SOC) of the battery. Because physics-based battery models (PBMs) can predict the performance decline caused by battery aging with high accuracy and robustness, a high-fidelity and reduced-order PBM is developed for battery SOC estimation according to the requirements of electric vehicle applications. The key model parameters are calibrated primarily according to low C-rate battery charging data. Based on the relationship between the lithium insertion ratios of the electrodes and the battery SOC, an SOC observer is designed. An adaptive cubature Kalman filter (ACKF) is combined with the reduced-order PBM to achieve adaptive tracking of the battery SOC. Three battery cells with different aging states are tested to verify the effectiveness of the proposed method. In addition, cycle aging experiments are conducted on a fresh battery for more than 1300 cycles. The experimental results reveal that the maximum error of SOC estimation is within 1.6% and the root mean square error is within 0.4% for both fresh and aged batteries.

Optimal Energy Management of Plug-In Hybrid Electric Vehicles Concerning the Entire Lifespan of Lithium-Ion Batteries

The performance of lithium-ion batteries will inevitably degrade during the high frequently charging/discharging load applied in electric vehicles. For hybrid electric vehicles, battery aging not only declines the performance and reliability of the battery itself, but it also affects the whole energy efficiency of the vehicle since the engine has to participate more. Therefore, the energy management strategy is required to be adjusted during the entire lifespan of lithium-ion batteries to maintain the optimality of energy economy. In this study, tests of the battery performances under thirteen different aging stages are involved and a parameters-varying battery model that represents the battery degradation is established. The influences of battery aging on energy consumption of a given plug-in hybrid electric vehicle (PHEV) are analyzed quantitatively. The results indicate that the variations of capacity and internal resistance are the main factors while the polarization and open circuit voltage (OCV) have a minor effect on the energy consumption. Based on the above efforts, the optimal energy management strategy is proposed for optimizing the energy efficiency concerning both the fresh and aging batteries in PHEV. The presented strategy is evaluated by a simulation study with different driving cycles, illustrating that it can balance out some of the harmful effects that battery aging can have on energy efficiency. The energy consumption is reduced by up to 2.24% compared with that under the optimal strategy without considering the battery aging.

Thermal runaway hazards investigation on 18650 lithium-ion battery using extended volume accelerating rate calorimeter

With the increase of lithium-ion batteries energy density and capacity, the thermal runaway (TR) is becoming a significant issue that can't be ignored. In this work, one kind of commercial 18650 lithium-ion battery with different states of charge (SOCs) and cycling times is used to evaluate the TR hazards by a ramp heating method in an extended volume accelerating rate calorimeter. Some thermal characteristic parameters are selected and analyzed from the experiment trails, such as the cell surface temperature, temperature rise rate, canister internal pressure and average canister surface temperature. The experiment results show that the maximum surface temperature of the battery and the maximum canister internal pressure increase with the increase of SOC when the TR occurs. The thermal energy released from the battery during TR is calculated using the initial and the maximum temperature on the battery and the canister surface. A fully charged fresh battery can release 61.72 kJ energy when it gets into TR, which could be converted to an explosion equivalent of 5.57 g TNT-equivalent. Compared with fresh batteries, aged batteries are more prone to get into TR and the TR hazards increase.