Precise High-Frequency Impedance Measurements of Cylindrical Battery Cells for Electric Vehicles

Characterization of battery cells and the creation of measurement-based models is a key step in the design process of battery packs for electric vehicles (EVs). Simulations of such models allow optimization of a battery pack design to minimize safety and functional errors that might appear late in the design stage and increase development time and cost. This paper demonstrates a method for measuring battery cell impedance with a vector network analyzer (VNA) under switch-controlled pulsed charge and discharge bias current and presents the resulting impact on the inductance of the cell at 108 MHz. The battery cell inductance under bias current at temperatures from -20°C to 40°C is presented. Finally, the bias current and temperature impact on the battery cell are shown.

Conventional cooling approaches that target either a singular tab or outer surface of common format cylindrical lithium-ion battery cells suffer from a high cell thermal resistance. Under an aggressive duty cycle, this resistance can result in the formation of large in-cell temperature gradients and high hot spot temperatures, which are known to accelerate ageing and further reduce performance. In this paper, a novel approach to internal thermal management of cylindrical battery cells to lower the thermal resistance for heat transport through the inside of the cell is investigated. The effectiveness of the proposed method is analysed for two common cylindrical formats when subject to highly aggressive electrical loading conditions representative of a high performance electric vehicle (EV) and hybrid electric vehicle (HEV). A mathematical model that captures the dominant thermal properties of the cylindrical cell is created and validated using experimental data. Results from the extensive simulation study indicate that the internal cooling strategy can reduce the cell thermal resistance by up to 67.8 ± 1.4% relative to single tab cooling, and can emulate the performance of a more complex pack-level double tab cooling approach whilst targeting cooling at a single tab.

The impedance behavior of a commercial Nickel-cobalt-aluminum(NCA) cylindrical cell was studied in this work. A series of impedance experiments was designed to explore the impact of battery state of charge (SOC) and other operating conditions. Our results indicated the impedance response of this cylindrical battery varies with the state of charge in both charge and discharge process. Experimental results also showed the SOC dependent impedance existed in different operating temperatures and C-rates. An impedance model was developed to explore the potential mechanisms behind experimental observations. Model results showed that the operating temperature and charge-discharge rate could significantly influence the impedance response of the battery but could not directly cause the variation of the impedance response at different SOC conditions. Results also showed that the contact resistance variation, resulted from the expansion and contraction of cell electrodes during charge and discharge, could lead to a SOC dependent impedance behavior of the commercial cell and influence battery output performance.

The production process chain of lithium-ion battery (LiB) cells consists of several interconnected process steps with many parameters that can influence the final properties and quality of the cells. In the development of cylindrical LiB cells, steps such as winding, cell assembly, filling, and formation play an important role in determining the properties of the intermediate product and the final performance of the battery cell. Continuous and low scrap production in the experimental stages of LiB battery cell production is challenging due to the limited understanding of cause-and-effect relationships. For example, the machine parameters that need to be configured depending on the properties of the input material. As a result, individual tuning of production machine settings for different materials is required. This is particularly critical in research pilot production environments, such as the BMW Battery Cell Competence Centre, where different materials are tested and experimental approaches are required to optimize the manufacturing processes. This paper presents an approach for utilizing data analytics and machine learning with Open Platform Communications Unified Architecture (OPC UA) and Internet of Things (IoT) data pipeline to better understand the relationships between process parameters, input material, intermediate product features and final quality in the production of cylindrical LiB battery cells. In this study, different machine learning algorithms were tested to predict the initial setpoints of the routing path and the gripper values from the parameters of the winding process and the characteristics of the input material in order to obtain an intermediate product with the desired quality. The best results were obtained using Random Forest Regression with an R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> of 0.976.

In our previous study overpotential resistances of nickel/metal-hydride and lithium-ion batteries were measured to estimate the battery temperature rises during rapid charge and discharge cycles by using our battery thermal model. However, the cell impedance measured by ac impedance meter did not agree with those induced by charge/discharge characteristics. Therefore, values were again measured by the method of Takano et al. [ J. Electrochem. Soc. , 147 , 922 (2000) ], who measured of lithium-ion batteries by Laplace transformation of both signals of the voltage-step input and its current response. This method has been extended here to Laplace transformation of current-step or current-pulse input and its voltage response to measure for any charge/discharge current of nickel/metal-hydride or lithium-ion battery. Nearly the same was obtained by the three different methods (voltage-step, current-step, and current-pulse inputs), and the measured did not depend on either the charge/discharge current or the state of charge/charge input. Moreover, the measured by the current-pulse method, which includes the Warburg impedance at low frequency, approaches the overpotential resistance that can provide a good estimate of the battery temperature rise in our battery thermal model.

This paper presents a highly precise battery impedance measurement algorithm. The proposed algorithm consists of fast Fourier transformations, peak, and phase difference estimations. Additional offset clipping and amplifying circuits expand the range of the signal measurement. An opamp based offset clipping circuit increases the ac ripple to DC voltage ratio without phase delay. Amplifying circuit gives more resolution to the ripple voltage. These proposed instrumentation ensure the precise measurement of ripple voltage and current. The proposed algorithm determines the peak magnitude of ripple voltage with tolerance of 0.12mV, and the phase difference tolerance is 0.2%. To validate the proposed approach, a 40Ah 13.6V Li-Ion battery charger was built using a Opal-RT controller, a synchronous buck converter, and offset clipping and amplifying circuits.

Thermal Management in Hybrid Power Systems Using Cylindrical and Prismatic Battery Cells

Impedance Analysis of Stem Cell-Derived Cardiomyocytes for Safety Screening and Drug Discovery

Lithium-ion batteries (LIBs) are commonly used in today’s electric vehicles. Studying their behaviour under mechanical loading, including short circuits, is vital for vehicle safety. This paper covers three major topics, (1) a general literature review for the state-of-the-art of LIBs, (2) physical cell tests for model validation are performed, wherein the occurrence of short circuits is detected and (3) creating a finite element model (FEM) of an 18650 cylindrical LIB using the most recent testing and simulation techniques. A variety of short-circuit criteria based on stresses, strains and geometric parameters have been implemented in the simulation and compared to the test results. It will be demonstrated that a combination of two geometric criteria, in the radial and axial directions of the cell, is best suited for virtual short-circuit detection in the simulation. Finally, the short-circuit criteria are implemented in a post-processing tool that allows fast short-circuit analysis of cells of different loadings. In the future, this method of short-circuit detection will be used to analyse an assembly of several battery cells such as, for instance, an automotive or maritime battery pack. Furthermore, the developed method enables mechanical integration with respect to crash safety in vehicles.

Phase change materials have been of increasing interest in thermal management of power batteries due to their high latent heat with minimum volume change. In this work, a numerical study of phase change materials is presented for the purpose of thermal control of the cylindrical power battery cells for applications in electric vehicles. Uniform heat density was applied at the battery cell surrounded by phase change material (PCM) of paraffin wax type contained in a metal housing. A two-dimensional cylindrical model was considered due to the model symmetry. The effects of power densities, heat transfer coefficients and onset melting temperatures were examined for the battery temperature evolution. Temperature plateaus can be observed from the present numerical analysis for the pure PCM cases, and the temperature level depending on the power densities, heat transfer coefficients, melting temperatures. In addition, the copper foam of high thermal conductivity was inserted into the PCM to enhance the heat transfer. The local thermal non-equilibrium between the metal foam and the PCM was taken into account in the numerical modeling. The significant thermal enhancement with copper foam was observed with lowered battery temperature.

Quasi steady state method to measure thermophysical parameters of cylindrical lithium ion batteries

Equivalent circuit has been widely used to simply the analysis for the motor, either conventional motor or special motor. Precision impedance measurement is the most important to the equivalent circuit analysis. Based on the principle of the motor equivalent circuit and the software LabVIEW, a low cost impedance measurement system for the motor production line is established because the impedance analytical instrument HP4294 is expensive. To test the equivalent impedance of USM, a low cost automatic impedance measurement system is established in this paper. The automatic system is combined with LCR3522 and communicated with PC computer in real-time through GPIB (general purpose interface bus). Not only the amplitude and the phase of the impedance, but also the inductance and the capacitance and the quality factor Q can be tested by this system in the same time. The system has succeeded in the measurement of the impedance-frequency relation of USM and the parameter of the no-brush director current motor. All these results from the data of the measurement are the basis of designing of the driving power, identification of the parameter of those motors. Also, the automatic measurement system applies a testing device for special motor such as USM in China.

Effective thermal management is crucial for maintaining the safety, performance, and lifetime of lithium-ion batteries (LIBs) in electric vehicles (EVs), particularly during high-current charge-discharge cycles that generate significant heat. This paper presents an experimental investigation and dimensionless theoretical analysis of a single-phase static immersion cooling system for cylindrical battery modules, a configuration rarely explored in the literature. Three dielectric fluids with different thermophysical properties, namely deionized water, RT22HC, and mineral oil, were tested in three cooling configurations: pure immersion, immersion with heat pipes (natural convection), and immersion with heat pipes combined with forced convection. A total of 24 cylindrical heat sources were tested at heat loads of 10–50 W, and key dimensionless parameters such as Rayleigh (Ra), Grashof (Gr), and Nusselt (Nu) numbers were calculated. Results show that increasing the heat load strengthens the natural convection due to buoyancy and increases the Nu value, with deionized water providing the most effective cooling. The integration of heat pipes and forced convection reduces the battery temperature by up to 34.22% (deionized water), which mathematically lowers the Nu value but significantly reduces the total thermal resistance of the system. This study is the first to validate the classical laminar Nu-Ra correlation (exponent = 0.246) for vertical cylindrical cells in a static immersion system, linking experimental findings and dimensionless modeling. The results provide practical guidance in fluid selection and configuration optimization for compact, passive, and energy-efficient battery thermal management systems in EV and stationary energy storage applications.

Biological Compatibility of Electromanipulation Media

Influence of cell voltage and current on sulfur poisoning behavior of solid oxide fuel cells