Electric Vehicle Battery Pack Research Articles

A dynamic material flow analysis of lithium-ion battery metals for electric vehicles and grid storage in the UK: Assessing the impact of shared mobility and end-of-life strategies

Limiting human-induced climate change represents a critical challenge for the future, and due to their disproportionate contribution to the problem, the energy and transport sectors are attracting the most attention in terms of emission reduction roadmaps and targets. Energy storage, particularly electrochemical storage, is poised to be a cornerstone in allowing those sectors to become more sustainable. This study presents the results of an integrated dynamic material flow analysis of the cumulative demand for lithium-ion battery metals (Li, Co, Ni and Mn) by the light duty vehicle and electricity generation sectors in the UK over the next three decades. Results have shown that recycling of end-of-life electric vehicle battery packs is very effective in “closing the loop”, and would enable driving the demand for all four metals back down to present levels by 2050, despite having achieved by then a complete shift to 100% electric vehicles. Additionally, repurposing end-of-life vehicle batteries for grid storage (with over 50 GWh of grid storage capacity expected to be in place by 2050) has been found to enable reducing purpose-built grid storage batteries to zero. Finally, an additional scenario analysis has indicated that a widespread behavioural shift from conventional vehicle ownership to shared mobility could even drive the demand for virgin battery metals into negative territory by 2040.

Development of hybrid thermal management techniques for battery packs

In this study, the thermal management issue of electric vehicle and hybrid electric vehicle battery pack is studied. Passive and hybrid techniques are developed and used in the battery pack. Multiple delta winglet vortex generators are introduced to enhance turbulence before the air flow interacts with the cells’ surface. Multiple jet inlets are introduced that enable the air flow to change its directions and pass through the dead air regions. A hybrid technique is also used in which a liquid jacket is added to each of the cells. The liquid within the jackets is in contact with the cells maximizing the contact surface area to improve heat transfer. Steady state computational fluid dynamic simulations are performed to study the effects of the passive and hybrid techniques added to the battery pack. The results indicate a substantial improvement in the temperature uniformity. The temperature difference of the hybrid battery pack reduces from 4.87 °C to 1.26 °C. Additionally, the temperature variance at the cell level reduces from 3.29 °C to 0.36 °C. This battery pack does not require moving parts and pumping power and it can achieve high levels of temperature uniformity.

Performance and Safety Evaluation of Lithium-Ion Batteries for Electric Vehicles

Performance and safety in battery packs are the major concern in the electrification sector. However, most of the research papers provide information, covering only one or very few parameters to describe the decrement of power and safety in the battery. It leaves aside a holistic and comprehensive study to critically evaluate performance in lithium-ion battery packs. This paper presents ten performance parameters with experiments and theory undertaken to understand the influence in power and safety in lithium-ion battery packs. The influence of performance parameters will provide and integrated approach to clearly identify the problems that induce decrement in performance and compromise safety in the battery. Comprehensive research of performance evaluation in electrification is nascent today, however, when the temperature and vibration parameters are critically reviewed, it has been found that a comprehensive effort is still required to evaluate the impact of vibration and temperature loads in the power performance and safety of lithium-ion battery packs for electric vehicles.

Research on Balanced Management Topology of Series Battery Pack

With the rapid development of renewable energy, energy storage battery technology has made great progress, and it has also caused the rapid development of electric vehicles. There is an inevitable difference between a large number of battery cells in the energy storage battery pack of electric vehicles. This difference will increase with time, and ultimately affect the safe operation of electric vehicles. Aiming at the problem of voltage imbalance in series battery packs, an improved balanced topology based on energy storage inductors is proposed. The basic working principle of the active balanced topology is analyzed, and the charging and discharging process of the balanced topology is theoretically derived. Finally, the simulation model of the balanced control during the charging and discharging process of the battery pack is built using MATLAB/Simulink. The simulation results show that the battery pack has a good balance effect during charging and discharging, which can provide an effective solution to the balance problem of series battery packs.

Experimental Study on the Mechanism of Thermal Runaway Propagation in Lithium-ion Battery Pack for Electric Vehicles

Experimental Study on the Mechanism of Thermal Runaway Propagation in Lithium-ion Battery Pack for Electric Vehicles

A Methodology to Model and Validate Electro-Thermal-Aging Dynamics of Electric Vehicle Battery Packs

A Methodology to Model and Validate Electro-Thermal-Aging Dynamics of Electric Vehicle Battery Packs

Multi-Battery Block Module Power Converter for Electric Vehicle Driven by Switched Reluctance Motors

To improve the endurance and charging flexibility of electric vehicle battery packs, this paper proposes a multi-battery block module (MBM) topology for four-phase switched reluctance motors (SRMs), which not only allows flexible electric vehicle operation, but also achieves fast demagnetization and excitation. By integrating the multi-battery block module and photovoltaic (PV) panel into an asymmetrical half-bridge (AHB) converter, the MBM topology is designed to supply a multilevel bus voltage for the SRM drive. To improve the endurance of battery packs, a PV panel is also added to the topology to charge battery packs when the system is stationary. According to the different operation requirements, multiple power supply modes and charging modes can be realized by controlling the power devices in the proposed MBM topology. The simulation results based on the MATLAB/Simulink platform and the experimental results on a four-phase 8 / 6 switched reluctance motor verify the effectiveness of the proposed design.

An Evaluation Framework for Second-Life EV/PHEV Battery Application in Power Systems

Energy storage is essential for balancing the generation and load in power systems. Building a battery energy storage system (BESS) with retired battery packs from electric vehicles (EVs) or plug-in hybrid electric vehicles (PHEVs) is one possible way to subsidize the price of EV/PHEV batteries, and at the same time mitigating forecast error introduced by load and renewable energy sources in power systems. This paper proposes a detailed framework to evaluate end-of-life (EOL) EV/PHEV batteries in BESS application. The framework consists of three parts. A generalized model for battery degradation is first introduced. It is followed by modeling the battery retirement process in its first life. Two vehicle types—EV and PHEV—as well as two retirement modes—nominal and realistic modes—are considered. Finally, the application of the second-life BESS in power systems is modeled in a detailed economic dispatch (ED) problem. This is how second-life BESS’s performance translates into cost savings on power generation. An optimization problem is formulated to maximize total cost savings in power generation over the battery’s second life. This is done by striking a balance between short-term benefit (daily cost savings) and long-term benefit (cost savings through service years). Numerical results validate the effectiveness of the proposed framework/models. They show that battery usage and retirement criterion in its first life directly affect the performance in its second life application. In our case study, EV battery packs possess larger EOL energy capacities and consequently generate more cost savings in the second life. However, the BESS built from retired PHEV batteries has higher cost savings per MWh. It is because, with the proposed degradation model, battery health is better preserved in PHEV applications. Compared to nominal retirement mode, realistic retirement mode results in extra cost savings due to the reduced first-life service years.

Modelling of modular battery systems under cell capacity variation and degradation

We propose a simple statistical model of electrochemical cell degradation based on the general characteristics observed in previous large-scale experimental studies of cell degradation. This model is used to statistically explore the behaviour and lifetime performance of battery systems where the cells are organised into modules that are controlled semi-independently. Intuitively, such systems should offer improved reliability and energy availability compared to monolithic systems as the system ages and cells degrade and fail. To validate this intuition, this paper explores the capacity evolution of populations of systems composed of random populations of cells. This approach allows the probability that a given system design meets a given lifetime specification to be calculated. A cost model that includes the effect of uncertainty in degradation behaviour is introduced and used to explore the cost-benefit trade-offs arising from the interaction of degradation and module size. Case studies of an electric vehicle battery pack and a grid-connected energy storage system are used to demonstrate the use of the model to find lifetime cost-optimum designs. It is observed that breaking a battery energy storage system up into smaller modules can lead to large increases in accessible system capacity and may lead to a decision to use lower-quality, lower-cost cells in a cost-optimum system.

A novel dielectric fluid immersion cooling technology for Li-ion battery thermal management

The objective of this study is to investigate direct cooling performance characteristics of Li-ion battery and battery pack for electric vehicles using dielectric fluid immersion cooling (DFIC) technology. The experimental results showed that Li-ion pouch cell immersed in flowing dielectric fluid assisted with tab cooling showed better cooling performance with 46.8% reduction in the maximum temperature at the positive tab compared to natural convection at 3C discharge rate. The electrochemical-thermal model of Li-ion pouch cell immersed in flowing dielectric fluid assisted with tab cooling was developed using Multi-Scale Multi-Domain (MSMD) approach with Newman, Tiedemann, Gu, and Kim (NTGK) model. A good agreement within ± 5% was found between the results of numerical study and experimental data. The 50 V battery pack maximum temperature was maintained below 40 °C for 5C discharge at the ideal pumping power of 81.7 W. With the application of the proposed DFIC assisted with tab cooling technology, the maximum battery pack temperature was 9.3% lower than the indirect cooling method, confirming the improved cooling performance compared to the conventional cooling method. Under thermal abuse condition with internal short circuit, the peak temperature of 341.7 °C was observed for the battery pack and thermal runaway of battery pack was prevented except the affected cell. This study demonstrated the DFIC assisted with tab cooling as a safe and efficient thermal management technology for high-density and high capacity Li-ion battery application in electric vehicles.

Online internal short circuit detection method considering equalization electric quantity for lithium‐ion battery pack in electric vehicles

The timely and accurate detection of an internal short circuit (ISC) is critical for improving electric vehicle (EV) safety. Typical ISC detection approaches are based on consistency differences between each cell in a module. However, the indispensable equalizer in a battery management system reduces inconsistency, affecting the accuracy and timeliness of ISC detection. Hence, an online ISC detection method considering equalization electric quantity (EEQ) is proposed. First, the remaining charge capacity and state-of-charge difference approaches are investigated. Next, the negative impact of EEQ on ISC detection is analyzed; thereafter, improved approaches based on EEQ compensation are proposed. Moreover, an ISC routing inspection approach for dormant EVs is proposed. Lastly, the proposed approaches are verified. The main results are as follow: (a) The ISC detection method without EEQ compensation has issues, such as significant errors, undetected ISC, and longer detection periods; our approaches help effectively overcome these issues, while the detection error is maintained below 5%; (b) Supplementing the above approaches, the proposed ISC routing inspection approach can help detect a moderate ISC even for a dormant EV, while further improving timeliness in ISC detection.

Investigation on liquid cold plate thermal management system with heat pipes for LiFePO4 battery pack in electric vehicles

An appropriate battery thermal management system is essential for electric vehicles to keep an optimal working temperature range with minimal temperature difference, and meanwhile to ensure the battery is more efficient and safe. In this paper, the liquid cold plate thermal management system with heat pipes is proposed to investigate the thermal characteristic of LiFePO4 battery pack during various discharge rate operations. A three-dimensional numerical model based on standard k-ε turbulent model is developed to realize the visible analysis of fluid flow and heat transfer for the proposed thermal management system. The 50 Ah battery module is used in the experiment to validate the cooling effects of proposed thermal management system relied on heat pipes, and its performance is compared with liquid cold plate without heat pipes. Furthermore, the cooling performance of the cold plate with heat pipes could be further improved through the orthogonal experiment design, the maximum temperature of battery cell and temperature difference of battery module could be dropped by 6.95% and 11.08%, as compared with the original design. What’s more, the channel height of cold plate with heat pipes has the greatest effect on the maximum temperature of battery cells and temperature difference of battery modules.

Simulation and Optimization of FEV Limit Discharge's Heat Dissipation Based on Orthogonal Experiments.

The temperature difference between batteries has effects on the performance of the battery packs of electric vehicles (EVs). Therefore, it is necessary to design a battery cooling management system. In order to reduce the maximum temperature difference of the cooling system of the Formula Electric Vehicle (FEV) automobile, the orthogonal experimental design method was adopted in this paper, and the temperature field of the FEV air-cooled cooling system structure under a short-time high-current discharge condition was simulated for many times. The maximum temperature difference after simulating optimization was about 7 K, and the overall optimization degree was close to 40%. The research results showed that the gap between the single battery and the battery pack was very important to heat dissipation.

Modeling the Impact of Active Material Volume Change on Accessible Capacity in Automotive Pouch Cells

Lithium-silicon chemistries show promise to increase battery capacity; however, silicon expands significantly during lithium intercalation, leading to inaccessible capacities as well as cell or pack failure due to pressure generation. Silicon-graphite (Si/C) composite anodes are used to increase the anode capacity while maintaining a tolerable degree of active material volume expansion. Recently, Dash and Pannala modeled anodes with increasing Si/C ratios and explored the tradeoff between increasing gravimetric capacity and the increasing active material volume expansion upon Li intercalation [1]. Their conclusion highlights that while the gravimetric capacity increases, there is ultimately a “threshold value” where the volumetric capacity will begin to decrease to account for the significant silicon volume expansion.This concept was built upon to account for electrochemical and mechanical design limitations applicable to battery packs for electric vehicles (EVs). We propose that increasing the Si/C ratio does not directly lead to an increase in the accessible capacity, because excessive volume expansion can lead to unacceptable cell pressure or electrode porosity. In order to predict the accessible capacity as a function of Si/C ratio, we integrated mechanical behavior for each individual cell component (e.g., composite anode, cathode, and foam packing) into our previous battery model [2-4]. This model can predict the split between changes in electrode porosity and dimensions by coupling component mechanical behavior to the volume change governed by electrochemical phenomena.In this presentation, we will focus on how the Si/C ratio will impact both mechanical and electrochemical behavior using our mechano-electrochemical model. Figure 1 shows an example of the pressure generation seen when considering (a) foam packaging and (b) a rigid volume for cells with varying percentages of Si in the anode. Accessible capacities of these materials can then be determined for a specific design’s pressure cutoff. Preliminary modeling of the links between active material Eeq, anode/cathode capacity balance, and volume change will also be discussed.

Pushing the Eenvelope in Battery Estimation Algorithms.

SummaryAccurate estimation of lithium-ion battery health will (a) improve the performance and lifespan of battery packs in electric vehicles, spurring higher adoption rates, (b) determine the actual extent of battery degradation during usage, enabling a health-conscious control, and (c) assess the available battery life upon retiring of the vehicle to re-purpose the batteries for “second-use” applications. In this paper, the real-time validation of an advanced battery health estimation algorithm is demonstrated via electrochemistry, control theory, and battery-in-the-loop (BIL) experiments. The algorithm is an adaptive interconnected sliding mode observer, based on a battery electrochemical model, which simultaneously estimates the critical variables such as the state of charge (SOC) and state of health (SOH). The BIL experimental results demonstrate that the SOC/SOH estimates from the observer converge to an error of 2% with respect to their true values, in the face of incorrect initialization and sensor signal corruption.

Feasibility Study for Sustainable Use of Lithium-Ion Batteries Considering Different Positive Electrode Active Materials under Various Driving Cycles by Using Cell to Electric Vehicle (EV) Simulation

Electric vehicles have been issued to achieve sustainable mobility. Main factors to sustainable electric vehicle (EV) are that lithium-ion battery (LIB) has to maintain lower cost, lighter weight, SOC (state of charge), thermal stability, and driving ranges. In this study, nickel-cobalt-manganese (NCM), lithium iron phosphate (LFP), and lithium manganese oxide (LMO), which are used as representative positive electrode materials, were applied to battery cells. Then, the battery characteristics at the system level, according to the application of different positive electrode materials, were compared and analyzed. To this end, each of the 18650 cylindrical battery cells was modeled by applying different positive electrode active materials. The battery modeling was based on a database provided by GT(Gamma Technologies)-AutoLion. To analyze the thermal stability and capacity loss according to the temperature of the battery cell by applying different C-rate discharge and temperature conditions for each positive electrode active material, an electrochemical-based zero-dimensional (0D) analysis was performed. A test was also performed to determine the model feasibility by using a MACCOR 4300 battery charger/discharger. Moreover, a lumped battery pack modeling was performed to extend the modeled battery cell to an EV battery pack. By combining the pack and one-dimensional (1D) EV models, various driving cycles were described to investigate the battery performance at the vehicle level. It was found that the 0D electrochemistry-coupled 1D vehicle model could well predict the feasible tendencies considering various positive electrode materials of the LIB battery cell.

Electrification in the automotive industry: effects in remanufacturing

The automotive market is changing. For many years, cars with internal-combustion engines were dominant. Recently, more cars with alternative drive trains have become available, and their market share has increased, a trend that has had an effect on the remanufacturing industry for automotive parts. This paper aims to describe and evaluate the challenges and opportunities in the coming years for the remanufacturing industry as a result of the increasing number and share of electric vehicles. Both theory and empirical data have been used to meet this aim. From theory, the two different drive train concepts of the internal combustion engine and the battery electric vehicle are described, along with the major differences from a remanufacturing standpoint. These differences and effects are described, evaluated, and fully or partly confirmed by industry experts. The results show that future market actors are unset today, less space-consuming machinery parks will be needed, major investments into knowledge and equipment (especially for testing) will be required, and the necessity to handle different kinds of end-of-use/life solutions, especially the recovery for the electric vehicle battery packs, will be a challenge. As future development is still uncertain, the authors recommend that market actors investigate the challenges and opportunities highlighted in this paper and watch future developments carefully.

The environmental footprint of electric vehicle battery packs during the production and use phases with different functional units

Battery electric vehicles (BEVs) have been widely publicized. Their driving performances depend mainly on lithium-ion batteries (LIBs). Research on this topic has been concerned with the battery pack’s integrative environmental burden based on battery components, functional unit settings during the production phase, and different electricity grids during the use phase. We adopt a synthetic index to evaluate the sustainability of battery packs. A life cycle assessment (LCA) is used to reveal the aspects of global warming potential (GWP), water consumption, and ecological impact during the two phases. An integrative indicator, the footprint-friendly negative index (FFNI), is combined with footprint family indicators of battery packs and electricity sources. We investigate two cases of 1 kg battery production and 1 kWh battery production to assess nickel–cobalt–manganese (NMC) and lithium–iron phosphate (LFP) battery packs and compare their degrees of environmental friendliness. Then, we break down the battery pack to identify the key factors influencing the environmental burden and use sensitivity analysis to analyze the causes. Moreover, we evaluate the environmental impact of battery packs during the use phase among different regions. Regardless of the functional unit (FU), the weights of the carbon footprint (CF), water footprint (WF), and ecological footprint (EF) are approximately the same. The results of the integrative environmental indicator, the FFNI, illustrate that the LFP is approximately 0.014, which is lower than that of the NMC battery pack in the mass production case. When using energy units as the FU, the FFNI of the NMC is 0.015, which reflects a lower environmental burden than that of other battery packs. In the use phase, 1kWh electricity consumption in China and Europe has the highest and lowest FFNI, respectively. When breaking down the battery-pack components, the simplified model advocates the cathode as the major contributor that determines the total environmental performance. In the following sensitivity analysis, the battery management system (BMS) is found to be the most intensive part of the footprint of most battery packs. FU can influence the evaluation results. Developing proper renewable energy sources can reduce the footprints of battery packs during the use phase. The positive electrode pastes in the battery cell, BMS, and packaging in the battery pack can influence the environmental burden. Adopting green materials in sections like the BMS may be a specific measure to enhance the environmental friendliness of a battery pack during the production phase.

Computationally-efficient thermal simulations of large Li-ion battery packs using submodeling technique

Accurate and rapid prediction of temperature distribution in a large Li-ion battery pack comprising thousands of cells is critical for ensuring safety and performance of battery packs for electric vehicles. Due to the multiscale geometry and the large number of individual cells in an automotive battery pack, full-scale thermal simulations typically take a long time to complete. Approaches for rapidly computing the temperature field in a large battery pack without significant loss of accuracy is, therefore, a key technological need. This paper presents thermal simulations of a large, air-cooled Li-ion battery pack containing thousands of individual cells using the submodeling technique. A coarse model that neglects fine geometrical details is first solved, and the results are used to solve a more detailed sub-model. It is shown that this approach results in 7X reduction in computation time while preserving the accuracy of the predicted temperature field. Trade-offs between computation time and accuracy are examined. The submodeling technique is used to investigate the thermal design of a large Li-ion battery pack, including the effect of discharge rate and coolant flowrate on temperature field, and the thermal response to a pulsed spike in discharge rate. Limitations of the submodeling technique are discussed. The technique discussed here is a general one, and may help significantly reduce computation time for thermal design and optimization of large, realistic Li-ion battery packs.

Multi-objective Optimization Design for Battery Pack of Electric Vehicle Based on Neural Network of Radial Basis Function (RBF)

As a carrier of EV batteries, battery pack is a key component that ensures stability, safety, and reliability of energy system for power batteries. In order to complete the requirement of light weight for EV, the battery pack shall have light weight as much as possible while meeting structural strength. This paper uses an Surrogate Models algorithm based on RBF neural network to solve the problem of multi-objective optimization for battery pack. It can be observed from LsDyna simulation results that the battery pack has declined 17.62% in mass and 30.78% in maximum deformation. Therefore, the proposed structure optimization model of battery pack hereof provides an effective design and optimization method for battery pack.