Automotive Battery Packs Research Articles

(Keynote) on the Challenges and Opportunities for Parameterizing Multi-Physics Battery Models with Expansion Measurements

Lithium-ion batteries are projected to reach cost targets making them competitive with internal combustion engines for light-duty transportation within the decade [1], which will help drive demand for EVs. Upcoming regulations in Europe, China, and the United States for automotive safety and durability will drive the design of battery systems, and the algorithms for battery management over the next decade. The Global Technical Regulation 20 (GTR20) describes the safety requirements for electric vehicle battery systems. In particular, the proposed regulation addresses the need for early detection and warning of occupants about battery faults and failures. The warning should allow for egress 5 minutes prior to the presence of a hazardous situation inside the passenger compartment caused by a battery cell thermal runaway. However, detecting the failure with enough time can be difficult using the current production battery sensor suites. Durability assessment for Lithium-ion batteries is also tricky because these systems are designed to live for more than 10-15 years, so testing under representative conditions could exceed multiple product development cycles. Accelerated aging tests can shorten the testing time to reach the product's end-of-life conditions, typically defined as 70 or 80% state of health, but a deep physical understanding of the degradation modes that are accelerated by the testing is required to project these results back to the real-world use case and warranty period. Due to the many possible definitions of battery State of Health (SoH) which can be related to both capacity loss and internal resistance growth, the Global Technical Regulation 22 (GTR22) defines their durability requirements in terms of two new related metrics: the State of Certified Energy (SOCE) and the State of Certified Range (SOCR). Both metrics represent a percentage of the certified battery energy or electric range remaining at a given point in time. The SOCE is based on the Society of Automotive Engineers (SAE) metric of Usable Battery Energy (UBE). The GTR22 will also require a way for the consumer to read battery health information and usage data from the vehicle. Physics-based battery models which include degradation mechanisms have great promise in addressing many of these challenges due to the relationship between modeled design parameters and the resulting device performance and durability. The models can enable virtual engineering to assess design tradeoffs before building the first prototype, however, parameterizing these models can be difficult due to the large number of parameters. In this presentation, we will explore the challenges of parameterizing physics-based battery models using conventional current, voltage, and temperature measurements. We will show how the measurement of the cell expansion in the laboratory setting and the fixtures that support the testing [2]. The augmentation of expansion data can inform model development and parameterization of a Single Particle Model with electrolyte dynamics (SPMe) implemented in the PyBaMM (Python Battery Mathematical Modelling) framework [3]. Next, we will demonstrate how the sensor data could be paired with the models to augment diagnostic algorithms to infer electrode-level aging phenomena, improve the state of charge estimation, and provide an early warning of gas generation before cell venting. Finally, we will discuss the practical implementation issues in packaging temperature and strain sensors in automotive battery modules and packs. [1] C. Shen, P. Slowik, A. Beach. “INVESTIGATING THE U.S. BATTERY SUPPLY CHAIN AND ITS IMPACT ON ELECTRIC VEHICLE COSTS.” Feb 2024, ICCT REPORT [2] S. Pannala, A. Weng, I. Fischer, J.B. Siegel, and A.G. Stefanopoulou, “Low-cost inductive sensor and fixture kit for measuring battery cell thickness under constant pressure.” 2022, IFAC-PapersOnLine, 55(37), 712-717. [3] Sravan Pannala et al 2024 J. Electrochem. Soc. 171 010532

Optimization and Structural Analysis of Automotive Battery Packs Using ANSYS

The development of new energy vehicles, particularly electric vehicles, is robust, with the power battery pack being a core component of the battery system, playing a vital role in the vehicle’s range and safety. This study takes the battery pack of an electric vehicle as a subject, employing advanced three-dimensional modeling technology to conduct static and dynamic analyses. Through weight reduction and structural optimization, an innovative power battery pack design scheme is proposed, aiming to achieve a more efficient and lighter electric vehicle power system. The main research tasks are as follows: Firstly, we designed the main load-bearing components of a certain electric vehicle’s power battery pack and established a three-dimensional (3D) model. Then, the model was simplified according to the actual stress conditions of the power battery pack of the electric vehicle and imported into finite element analysis (FEA) software. Next, based on the fundamental principles of the finite element method (FEM), we conducted static analyses under three conditions: bumpy road sharp left turn, bumpy road sharp right turn, and bumpy road emergency braking. The analysis results indicate that the strength of the battery pack meets the allowable requirements, suggesting that the lower housing design has significant redundancy, providing guidance for subsequent optimization. Finally, through modal analysis, we extracted the first six modes of the power battery box, with the first mode frequency being 33.69 Hz. This suggests that the battery pack may experience resonance during actual operation. Based on the static and modal analysis results, we proposed a structural optimization and lightweight design solution for a certain electric vehicle battery pack and compared it with the pre-optimization data.

Distributed fiber optic strain sensing for structural health monitoring of 70 MPa hydrogen vessels

We report on the development and testing of 70 MPa hydrogen pressure vessels with integrated fiber optic sensing fibers for the automotive use. The paper deals with the condition monitoring of such composite pressure vessels using the optical backscatter reflectometry (OBR) which was applied for a distributed fiber optic strain sensing along fully integrated polyimide-coated single-mode glass optical fiber (SM-GOF). The sensing fibers were embedded into the vessel structure by wrapping them over the inside polymer liner during the manufacturing process of the outside carbon fiber reinforced polymer (CFRP). Detecting local strain events by the integrated fiber optic sensors might be an opportunity for monitoring the material degradation. Regarding the investigation of the ageing behavior, both ambient hydraulic cycling tests and slow burst tests were conducted on 70 MPa pressure vessels with embedded fiber optic sensors. The achieved results contribute to the knowledge about material fatigue to guarantee the safe usage during the entire lifetime of the composite hydrogen storage vessels. The presented work stands in context of the European Horizon 2020 research project SH2APED focused on the development of an innovative hydrogen storage system composed of an assembly of nine 70 MPa tubular pressure vessels used as an automotive battery pack.

Safety risk assessment for automotive battery pack based on deviation and outlier analysis of voltage inconsistency

Safety risk assessment is essential for evaluating the health status and averting sudden battery failures in electric vehicles. This study introduces a novel safety risk assessment approach for battery systems, addressing both cell and pack levels with three key indexes. The core of the assessment lies in representing the relative deviation of cell voltages through scatter diagrams across various stages of service life. Specifically, the study quantifies voltage deviations and deviation angles within different state of charge intervals to gauge safety risks at the cell level. Leveraging clustering algorithms aids in identifying outlier values. Furthermore, the dispersion of scatter points is utilized to assess safety risks at the pack level. Validation of this proposed model is conducted through cycling tests on battery modules with a deformed cell, demonstrating its efficacy in capturing inconsistent features of mechanical deformation abuse across the three indexes, thereby triggering alarms during operation. Moreover, the method is applied to assess the safety risks of five hazardous and accident-prone vehicles, enabling comprehensive evaluation of potential faulty cells and safety risks at the pack level. This proposed approach offers a fresh perspective on the comprehensive safety risk assessment of battery systems.

Detection and isolation of faults in a lithium-ion battery pack using a switched architecture of equivalent cell diagnosers

Lithium-ion battery packs are typically built as a series network of Parallel Cell Modules (PCM). A fault can occur within a specific cell of a PCM, in the sensors, or the numerous connection joints and bus conductors. This paper presents a method of detecting a single occurrence of various common faults in a Lithium-ion battery pack and isolating the fault to the faulty PCM, its connecting conductors, and joints, or to the sensor in the pack using a Diagnostic Automata of configurable Equivalent Cell Diagnosers. This is achieved by activating a sequence of diagnosers that generate residuals for various sub-networks of the pack and test hypotheses on them to search for the smallest sub-network and the associated sensors that contain the source of the fault. The sequence of activation of the diagnosers follows the state transition of the Diagnostic Automata triggered by the outcomes of the hypotheses tests. Once the faulty PCM sub-network is identified, the fault type is classified based on selected features of the residuals. For robust detection, events arising from hypothesis tests in the diagnosers and the classifiers are used to compute the probability of occurrence of a specific fault in a specific PCM. The performance of the diagnostic framework is tested offline with experimentally obtained data from an automotive battery pack. Finally, a Hardware-in-the-Loop simulation test demonstrates that the proposed method can be implemented on standard Battery Management System hardware to avoid extensive damage to the pack, enhance safety, and facilitate quick cell-level replacements to repair expensive Lithium-ion battery packs.

A modelling approach for laser welding of busbars to lithium-ion prismatic cell terminals to enhance failure prediction

Laser welding is increasingly being used to connect automotive battery packs and weld busbars to prismatic cell terminals due to its ability to weld a wide variety of materials at high speed. The choice of material for the connecting busbars is primarily based on weldability, weight, electrical/thermal conductivity and cost. Aluminum (Al) is increasingly being chosen as busbar material to meet these criteria. This paper investigates laser overlap welding of Al for producing busbar-to-terminal interconnects for prismatic cell assembly. To understand the strength of these laser-welded joints in the early stages of design, the joints must be modelled. In addition, the structural modelling of battery module connections is critical to understanding the impact resistance (crash safety) of electric vehicles. Fusion-based modelling of laser welding is computationally inefficient and difficult to integrate into large structural models e.g., full vehicle crash models. Instead, it is more computationally efficient to generate a structural model of the weld, tuned to experimental test data, which can be easily integrated into larger models. LS-DYNA was employed to model the mechanical behavior of 1 mm to 1 mm AA1050 laser welds. Welding was performed using a wobble head integrated with a 1 kW CW fiber laser system. The simulation is based on laser weld with a rectangular pattern and was developed from experimental data from lap shear, T-peel, cross-tension and torsion tests. This modelling approach was extended to obtain joint strength for laser welding a 1.5 mm 1060 Al busbar to a 4 mm 1060 Al prismatic cell terminal. The predicted load–displacement curves closely matched the test data.

Laser-based battery pack disassembly: a compact benchmark analysis for separation technologies

The global decarbonization will have to be driven by the e-mobility sector to achieve the climate goals. End-of-life battery packs therefore need to be recycled efficiently and sustainably so that a cost-competitive circular economy can be adopted. In current process approaches, once the battery is discharged, disassembly is typically performed manually in a process that is not automated and dangerous to workers. To disassemble, first the battery cover must be removed, whereby current technological approaches focus on screw connections, which are difficult to loosen due to their condition after many years in the vehicle and cause poor automation capability. Another alternative is to mechanically mill the battery cover, which creates chips inside the battery pack that can cause short circuits. Waterjet cutting, which is also a process approach, faces the challenge of water getting into the battery pack, which can also lead to short circuits. Therefore, there is a need for new technological approaches which can dismantle an automotive battery pack productively with enhanced safety standards for workers and batteries. For this purpose, this paper performs a compact benchmark analysis of different separation technologies to identify initial potentials and challenges for laser-based disassembly of automotive battery packs.

Wire bond contact defect identification in battery modules of electric vehicles using pulses and differential voltage analysis

Automotive battery packs for electromobility applications consist of a large number of interconnected battery cells. Different cell-to-busbar joining techniques are utilized, with cylindrical cells frequently being contacted using wire bonding. Failure of individual connections can occur due to strong vibrations during operation and improper stress, making detection by the battery management system a necessity. This study investigates the identification of an electrical wire bond failure in a state-of-the-art electric vehicle module of a Lucid Air with 10 series-connected and 30 parallel-connected cells (10s30p). Four individual cells were characterized extensively in order to generate a simulation model taking into account parameter scatter. The failure case under investigation was simulatively incorporated in one parallel circuit and subsequently replicated in experimental validation measurements at the module level. The results show that this defect can be detected using pulses of C/3 or higher currents at various states of charge. An even more robust detection is achieved using differential voltage analysis of constant current C/20 discharge voltage trajectories. This defect identification method does not require any additional measurement sensors beyond the voltage taps and sensors provided by the manufacturer – with one voltage sensor per parallel circuit – and can therefore be implemented during electric vehicle usage, e.g. at dedicated service checks. A discussion on the applicability and scalability as well as the limitations of the method is provided. All measurement data of the state-of-the-art Lucid battery system is available as open source alongside the article.

Multi-objective lightweight design of automotive battery pack box for crashworthiness

To study an efficient lightweight method of electric vehicle power packs, the paper proposes that a hybrid method is combined with the modified Genetic Algorithm (NSGA-II), the contribution analysis method and the TOPSIS method for improving the battery pack enclosure (BPE) crashworthiness and reducing the structural mass. First, the finite element model of BPE and the crushing crashworthiness model were established and effectively verified by constrained modal analysis and crushing tests. Next, the initially selected optimized components were screened with the contribution analysis method to identify the final optimized components with thickness as the design variable. Also, the battery pack structure values at a design point with the Latin hypercube sampling are obtained. Moreover, the response surface (RSM) agent model was used to construct a relationship between optimization indicators and the design variables. Based on that, this paper carried out the multi-objective optimization design of NSGA-II algorithm and obtained the optimal compromise solution by TOPSIS method. And finally, by numerical simulation, the optimization results were verified and compared with the initially designed BPE. The results showed that the optimized battery pack components reduced the total weight by 4.31% and the crushing deformation of the box by 5.97%.These results contribute to the lightweight and crash-resistant BPE design with excellent performance.

Influences on Vibration Load Testing Levels for BEV Automotive Battery Packs

Battery Electric Vehicles (BEVs) have an increasingly large share of the vehicle market. To ensure a safe and long operation of the mostly large underfloor-mounted traction batteries, they must be developed and tested in advance under realistic conditions. Current standards often do not provide sufficiently realistic requirements for environmental and lifetime testing, as these are mostly based on data measured on cars with an Internal Combustion Engine (ICE). Prior to this work, vibration measurements were performed on two battery-powered electric vehicles and a battery-powered commercial mini truck over various road surfaces and other influences. The measurement data are statistically evaluated so that a statement can be made about the influence of various parameters on the vibrations measured at the battery pack housing and the scatter of the influencing parameters. By creating a load profile based on the existing measurement data, current standards can be questioned and new insights gained in the development of a vibration profile for the realistic testing of battery packs for BEVs.

DC Charging Capabilities of Battery-Integrated Modular Multilevel Converters Based on Maximum Tractive Power

The increase in the average global temperature is a consequence of high greenhouse gas emissions. Therefore, using alternative energy carriers that can replace fossil fuels, especially for automotive applications, is of high importance. Introducing more electronics into an automotive battery pack provides more precise control and increases the available energy from the pack. Battery-integrated modular multilevel converters (BI-MMCs) have high efficiency, improved controllability, and better fault isolation capability. However, integrating the battery and inverter influences the maximum DC charging power. Therefore, the DC charging capabilities of 5 3-phase BI-MMCs for a 40-ton commercial vehicle designed for a maximum tractive power of 400 kW was investigated. Two continuous DC charging scenarios are considered for two cases: the first considers the total number of submodules during traction, and the second increases the total number of submodules to ensure a maximum DC charging voltage of 1250 V. The investigation shows that both DC charging scenarios have similar maximum power between 1 and 3 MW. Altering the number of submodules increases the maximum DC charging power at the cost of increased losses.

Progress and Perspective of Ultra-High-Strength Martensitic Steels for Automobile

With the background of emission peaks and carbon neutrality, light weight has become an irreversible trend in the development of the automobile industry. It is an inevitable choice to use a large amount of ultra-high-strength steels to realize light weight and safety of automobiles. Ultra-high-strength martensitic steels can be divided into hot-formed steels and cold-formed steels according to the forming process. In recent years, ultra-high-strength martensitic steels have been rapidly developed in automotive battery pack frameworks, door guard beams, bumpers, A-pillars, etc., depending on their good plasticity and advanced forming technology. In this paper, the recent progress of ultra-high-strength martensitic steels for automobiles is systematically reviewed, the mechanisms of alloying, strengthening, and toughening are emphatically expounded, and the hydrogen embrittlement problems in application are summarized. Finally, the prospects of manufacture and application of ultra-high-strength martensitic steels for automobiles in the future are forecasted.

Life cycle assessment of recycling options for automotive Li-ion battery packs

Ramping up automotive lithium-ion battery (LIB) production volumes creates an imperative need for the establishment of end-of-life treatment chains for spent automotive traction battery packs. Life Cycle Assessment (LCA) is an essential tool in evaluating the environmental performance of such chains and options. This work synthesises publicly-available data to expand upon previously reported LCA studies for LIB recycling and holistically model end-of-life treatment chains for spent automotive traction battery packs with lithium nickel cobalt manganese oxide positive electrodes. The study provides an in-depth analysis of unit process contributions to the environmental benefits and burdens of battery recycling options and integrates these with the battery production impacts to estimate the net environmental benefit achieved by the introduction of recycling in the value chain. The attributional LCA model accounts for the whole recycling chain, from the point of end-of-life LIB collection to the provision of secondary materials for battery manufacturing. Pyrometallurgical processing of spent automotive traction battery cells is predicted to have a larger Global Warming Potential (GWP), due to its higher energy intensity, while hydrometallurgical processing is shown to be more environmentally beneficial, due to the additional recovery of lithium as hydroxide. The majority of the environmental benefits arise from the recovery of aluminium and copper fractions of battery packs, with important contributions also arising from the recovery of nickel and cobalt from the battery cells. Overall, the LCA model presented estimates a net benefit in 11 out of 13 environmental impact categories based on the ReCiPe characterisation method, as compared to battery production without recycling. An investigation of the effect of geographic specificity on the combined production and recycling indicates that it is as a key source of GWP impact variability and that the more climate burdening chains offer a significantly higher potential for GWP reductions through battery recycling. The sensitivity analysis carried out shows that impacts related to air quality are higher when recovering lower grade materials. This study provides a quantitative and replicable inventory model which highlights the significance of the environmental benefits achieved through the establishment of circular automotive battery value chains.

Optimization of automotive battery pack casing based on equilibrium response surface model and multi-objective particle swarm algorithm

Lightweight research based on battery pack structural strength can improve the endurance and safety of electric vehicles. Based on the adaptive response surface and multi-objective particle swarm optimization algorithm, this paper proposes an optimization design method for lightweight of battery pack shell. The thickness of the battery pack shell is the optimization parameter. The stress, strain, and frequency of the battery pack shell under typical working conditions are used as boundary conditions. The response surface model is established according to the criterion of cross terms in adaptive response surface method, and the multi-objective particle swarm optimization algorithm is used for iterative solution. The optimization results show that the maximum stress of the battery pack is reduced to the appropriate range, the first-order frequency is increased by 41% to reduce resonance, the maximum deformation is reduced from 2.7 to 1.12 mm, and the total mass is reduced by 26.8%. The battery pack optimization design method proposed in this paper can achieve lightweighting while meeting safety performance.

Modelling the impact of laser micro-joint shape and size on resistance and temperature for Electric Vehicle battery joining application

Laser micro-welding is increasingly being used to produce electrically conductive joints for automotive battery packs or energy storage devices to weld tabs to cylindrical cell terminals or pouch cell tabs to a busbar. There is little research currently existing in the literature reporting the joint characteristics in terms of electrical resistance and temperature rise due to charge-discharge current. This paper focuses on characterising and modelling electrical and thermal behaviours of laser micro-welds considering different shapes and sizes of the welding seam. A wide variety of laser joint shapes, including linear seam, multiple laser spots, circular seam, cross-seam and square seam were investigated with varying seam sizes considering 0.3 mm copper and Hilumin steel tab materials. Results showed that under-weld, good-weld and over-weld had a high impact on mechanical strength and fusion zone characteristics, however, the electrical resistance and temperature rise behaviours were not influenced by these weld categories. The linearized resistivity model was able to capture the effect of Joule heating and predicted resistance and temperature behaviours within ±6% error. The suitability of multiphysics electrical and thermal modelling for predicting the resistance and temperature behaviours at the early design stage has been demonstrated.

Characteristics and Hazards of Plug-In Hybrid Electric Vehicle Fires Caused by Lithium-Ion Battery Packs With Thermal Runaway

Fire accidents constitute a significant safety concern for automotive lithium-ion battery packs and have impeded the development of electric vehicles (EVs). While fire safety concerns have been raised about EVs, their fire performance remains unknown, especially for plug-in hybrid electric vehicles (PHEVs). Hence, this paper conducted full-scale fire experiments of PHEVs to explore their fire behavior and characteristics. Two brand new PHEVs were employed, and their power battery packs were ignited as the origin of the fire to simulate the representative fire scenario. Results showed that visible flames appeared around the chassis after about 60 min of the experimental procedure. Around the fire emerged, the battery packs intermittently released plenty of white smoke, which induced gas-phase explosions. The main component of the smoke was combustible gases. The SUV-type PHEV test took 9 min 11 s for the chassis flames to evolve into a passenger compartment fire. Due to the slow propagation of the fire in sedan-type PHEV, it required 9 min 56 s for flames to engulf the rear part of the sedan. The maximum temperature of PHEV fires was 843.6°C, while the maximum height of the fire reached around 3 m. At a distance of 1 m, the radiative heat emitted from burning PHEVs peaked at 1.151 kW/m2. Moreover, some secondary hazards of PHEV fires were illustrated. These results stimulate future experiments seeking novel flame retardant materials for PHEVs and provide helpful guidance on screening reliable PHEV fire prediction and protection strategies.

Macro-Modelling of Laser Micro-Joints for Understanding Joint Strength in Electric Vehicle Battery Interconnects.

Laser micro-welding is increasingly being used to produce electrically conductive joints within a battery module of an automotive battery pack. To understand the joint strength of these laser welds at an early design stage, micro-joints are required to be modelled. Additionally, structural modelling of the battery module along with the electrical interconnects is important for understanding the crash safety of electric vehicles. Fusion zone based micro-modelling of laser welding is not a suitable approach for structural modelling due to the computational inefficiency and the difficulty of integrating with the module model. Instead, a macro-model which computationally efficient and easy to integrate with the structural model can be useful to replicate the behaviour of the laser weld. A macro-modelling approach was adopted in this paper to model the mechanical behaviour of laser micro-weld. The simulations were based on 5 mm diameter circular laser weld and developed from the experimental data for both the lap shear and T-peel tests. This modelling approach was extended to obtain the joint strengths for 3 mm diameter circular seams, 5 mm and 10 mm linear seams. The predicted load–displacement curves showed a close agreement with the test data.

Optimization of liquid cooling and heat dissipation system of lithium-ion battery packs of automobile

A stable and efficient cooling and heat dissipation system of lithium battery pack is very important for electric vehicles. The temperature uniformity design of the battery packs has become essential. In this paper, an optimization design framework is proposed to minimize the maximum temperature difference (MTD) of automotive lithium battery pack. Firstly, the cooling channels of two cooling and heat dissipation structures are analyzed: serpentine cooling channel and U-shaped cooling channel. The results show that the serpentine cooling channel has better cooling effect. Secondly, the adaptive ensemble of surrogate models based on an improved particle swarm optimization algorithm is proposed to aid the optimization design of the serpentine cooling channel. The results show that the maximum temperature difference of the optimized scheme is reduced by 7.49% compared with the initial scheme, and the temperature field distribution of the lithium battery pack is more uniform. The proposed optimization design framework has certain guiding significance for the liquid cooling design of the battery packs.

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.

Local degradation and differential voltage analysis of aged lithium-ion pouch cells

Abstract Knowledge of the underlying degradation mechanisms in a lithium-ion cell is crucial for the development process and control of automotive lithium-ion battery packs. In this paper, a local post-mortem degradation analysis is performed on two differently cycled large-format pouch cells to improve the understanding of the underlying degradation mechanisms. For each cell, anode and cathode sheets are extracted and electrode coins are cut out from the sheets in an equally spaced, five-by-five pattern to assemble three-electrode test cells. Subsequently, the local capacities and differential voltage curves of the test cells are determined showing an inhomogeneous loss of lithium inventory for one cell and a capacity degradation of the cathode for the other cell. In a parallel connection of the test cells, the influence of the degradation mechanisms on the pouch cell’s differential voltage curve is shown and an approach is validated for calculating the resulting differential voltage curve by superimposing the single measured curves. In addition, the local discharge resistance is evaluated, revealing for both aged cells that the measured resistance increase at pouch cell level is the result of an increased resistance of the cathode and a decreased anode resistance.