Battery Pack Configurations Research Articles

A strategy to assess the use-phase carbon footprint from energy losses in electric vehicle battery

The electric vehicles are not completely emission-free. The vehicles consume power and the power generation processes involve carbon emissions, resulting in indirect vehicle usage carbon emissions. A use-phase carbon emissions assessment can help electric vehicle designers and manufacturers analyze the onboard carbon footprint and mitigate vehicle-related carbon emissions through energy consumption optimization. In this article, we focus on the use-phase carbon footprint based on the energy losses in electric vehicle battery packs. A battery pack energy loss model is established to examine the carbon footprint of four main subsystems of the battery pack, including the energy storage system, thermal management system, and battery junction box. We use the proposed method to evaluate the battery pack use-phase carbon emissions in four different cities from four main continents. The results show that the highest emissions appear in Tokyo (436.2 kgCO2) due to the relatively high greenhouse gas factor on the grid, the London has the lowest 207.5 kgCO2 emissions due to the massive adoption of sustainable energy during power generation. With a similar high greenhouse gas factor, but Sydney shows lower emissions (347.5 kgCO2) compared to Tokyo, which illustrates the closer the annual average temperature to the battery suitable operation range, the lower energy loss happens inside the battery pack due to the low thermal management load and resistance energy loss in the cells. This electric vehicle has the highest energy loss rate (20.8%) in New York, 343.6 kgCO2 emissions, and the highest thermal management system energy losses show the high seasonal temperature difference causing the high thermal management load to maintain the battery temperature. The proposed method can be used for different battery pack configurations and vehicle uses, providing researchers with a robust and versatile use-phase carbon emissions assessment strategy.

Modeling venting behavior of lithium-ion batteries during thermal runaway propagation by coupling CFD and thermal resistance network

Thermal runaway (TR) seriously hinders the wide application of lithium-ion batteries. One of the most significant hazards of TR lies in the emission of flammable gases, which might cause explosion in the battery pack. A TR model incorporating venting provides insights into reducing explosion risk and aids to determine the safety-optimal configuration of battery pack. In this study, a modeling framework is proposed to address gas venting and explosion hazard by coupling CFD and thermal resistance network. The TR propagation is predicted by a lumped network integrating heat generation and jet dynamics while the transport of gases is simulated by the CFD models. The developed model was confirmed by cell temperatures and gas concentrations measured by experiments and then adopted to examine the influence of various configurations of battery pack. Results demonstrate increasing ventilation rate can decrease the gas concentration and shorten the duration of battery pack under explosion whereas a limited effect of void volume is evident for that. Despite of reducing TR propagation speeds, the increase of cell distance can inhibit the rapid dispersion of venting gases, causing battery pack exposed to a prolonged explosion risk. The present model represents the further optimization of battery pack from the aspect of safety.

Detection of inhomogeneities in serially connected lithium-ion batteries

Serially connected batteries present a cell-to-cell variation in their electrochemical behavior that tends to increase over the lifetime. The decision for the best circular economy option for aged or defective battery packs – i.e., repair, remanufacturing, or recycling – requires comprehensive testing, analysis, and an according data basis. Remanufacturing of battery packs refers to the replacement of individual (sub-)modules or cells which are defective or show a diverging aging behavior to the rest of the battery units. A detection algorithm is required to decide if a significant inhomogeneity in a serial connection of batteries is present. For this reason, virtual battery packs are built based on the measurement of 12 individual batteries of the same type. Cell-to-cell variations are determined at the begin of life and a novel representation for the quantitative and qualitative analysis is given. This work extracts impedance-based features of different serial battery pack configurations through a novel comparative analysis approach. The features are extracted from Bode and Nyquist plots and the real and imaginary parts of the impedance itself. The detectability is analyzed depending on the number of cells and the underlying effects are discussed. A detailed sensitivity analysis is carried out for the most promising features, in which the influence of the cell-to-cell variations, the aging condition, and the aging mechanism are analyzed. The feature that shows the highest sensitivity, the so called low-frequency minimum, is able to detect single outliers within a high number of serially connected cells.

A comparative study of equivalent circuit models for a Li-ion battery pack of an electric Tuk-Tuk

This paper presents developments and validations of Lithium Nickel Manganese Cobalt Oxide (NMC) battery cell and battery pack models. A 7.4 kWh NMC battery pack is installed on an electric Tuk-Tuk equipped with a 3 kW motor. The battery pack is configured of four cells connected in parallel and 20 sets of the four cells connected in series. Based on the first-order and the second-order equivalent circuit models, battery cell and battery pack models are developed in Matlab/Simulink environment. For parameter identifications of the cell model, pulse discharge tests are performed at room temperature with 10% State of Charge (SOC) interval. The lumped heat capacitance method is applied to the battery models. The battery cell model is validated with SOC, cell center temperatures and terminal voltage using the experimental data of constant current discharge tests. With the battery pack configuration, the battery cell model is scaled up to match the battery pack voltage and its capacity. The dynamics of the battery pack models are validated with the vehicle testing data using the no-load, wide-open throttle and real road tests. The simulation results show good agreement with the test data. Using the developed battery models, vehicle performance and its energy consumption can be improved by optimizing battery cell and pack configurations.

Resistive Force Calculation and Battery Pack Configuration using Simulink Model

This paper provides a step by step guide for calculation of powertrain unit including the configuration of battery pack of a two-wheeler electric vehicle. Based on the design and desired performance of the vehicle, the total resistance force, torque and power is calculated and designed in MATLAB and Simulink, which is essential for selection of electric motor. Knowing the voltage and capacity of an individual cell the configuration of battery pack is calculated and depicted in SOLIDWORKS Computer Aided Design model. A website is developed which is competent to perform the necessary calculations and display the output of the desired performance parameters.

Power Hardware in the Loop (PHIL) Simulation of Battery Packs

Testing battery pack configurations for their performance under different dynamic load profiles for grid and electric vehicle applications is expensive. Lowering the cost to understand the response of packs and their control strategies is critical. Power hardware in the loop (PHIL) simulation is widely used in power engineering for system and component testing. A simulator computes the model output in real-time, and then controls a power source to generate a dynamic power output with the expected current and voltage response of the emulated battery pack. This emulated battery pack power output can be coupled to a physical load to perform testing.1 Small time steps are useful to observe the transient response of the emulated battery when there is a sudden change in the load. PHIL simulations can also be useful to study the transient response of controllers and inverters present in the battery management system by connecting these devices to the simulator. PHIL simulations can be used to test the model’s accuracy2, to conduct repeatability experiments and to test battery performance under extreme conditions without compromising on safety.3 It provides an efficient approach to designing and testing new configurations of batteries from data of a single cell without building their real prototypes. The computational speed required to solve the battery models chosen for PHIL simulations must be fast in order to achieve real-time implementation. Therefore, models chosen for these simulations tend to have less complexity. However, to provide a better understanding of a battery’s response under a specific load profile, it is necessary to use a model that that accurately represents the behavior of a real battery. Real-time simulations for physics-based battery models have been explored in the past.4 , 5 , 6 It is also essential to comprehend how different battery architectures and how aging affects the overall performance. In literature, equivalent circuit models that describe charge transfer and diffusion dynamics have been used as the main way to capture battery dynamics.7 , 8 We first show results generated using SIMULINK equivalent circuit models that are compiled to run fast on our Opal-RT real-time simulator. The Opal-RT simulator drives an AMETEK 40 kW power supply with feedback to the model, enabling an emulated battery pack response capable of 10ms dynamic control. We evaluate pack configurations with physical parameters that correspond to either LCO or NMC 18650 cells. Overall, this represents a 400V, 10kW pack. A programmable load is used to modulate the emulated battery pack and monitor its dynamic response. We further explore implementing single particle models with our PHIL simulations to help understand the internal dynamics of the cell captured by these models. Physics-based models have rarely been used for PHIL. Our results show that the PHIL emulation of the battery pack meets the expectations for the battery dynamics. However, we observe high frequency noise in the output signal of the emulated battery pack. Because this level of noise is not a trait present in real battery packs, we are exploring signal processing methods to filter and remove it, while retaining the essential dynamics of the emulated battery pack. References A. Viehweider, G. Lauss, and L. Felix, Simul. Model. Pract. Theory, 19, 1699–1708 (2011).Y. He, W. Liu, and B. J. Koch, J. Power Sources, 195, 2969–2974 (2010).H. Dai, X. Zhang, X. Wei, Z. Sun, J. Wang, and F. Hu, Electr. Power Energy Syst., 52, 174–184 (2013).P. W. C. Northrop, V. Ramadesigan, S. De, and V. R. Subramanian, J. Electrochem. Soc., 158, A1461 (2011).V. R. Subramanian, V. Boovaragavan, V. Ramadesigan, and M. Arabandi, J. Electrochem. Soc., 156, A260 (2009).P. W. C. Northrop, V. Suthar, Bharatkumar Ramadesigan, S. Santhanagopalan, R. D. Braatz, and V. R. Subramanian, J. Electrochem. Soc., 161, E3149 (2014).J. V. Barreras, C. Fleischer, A. E. Christensen, M. Swierczynski, E. Schaltz, S. J. Andreasen, and D. U. Sauer, IEEE Trans. Ind. Appl., 52, 5086–5099 (2016).H. Song, T. Kim, J. Jeong, B. Kim, D. Shin, B. Lee, and H. Heo, IET Power Electron., 6, 417–424 (2013).

Analysis of Cooling Effectiveness and Temperature Uniformity in a Battery Pack for Cylindrical Batteries

In this paper, techniques to improve cooling and temperature uniformity in a simple battery pack are examined. Four battery pack configurations are developed. In the first configuration, an inlet plenum is added to a simple battery pack. In the second configuration, jet inlets are incorporated along with the inlet plenum, and in the third configuration, multiple vortex generators are added in addition to the inlet plenum. Finally, in the fourth configuration, an inlet plenum, jet inlets, and multiple vortex generators are incorporated into the battery pack. The results conclude that by adding inlet plenum, multiple vortex generators, and jet inlets in the same configuration, significant improvements are observed. The results also show that the maximum temperature of the battery pack is reduced by ~5%, and the temperature difference between the maximum temperature and the minimum temperature exhibited by the battery pack is reduced by 21.5%. Moreover, there is a ~16% improvement in the temperature uniformity of a single cell.

Contribution to the Study of Electric Arcs in Lithium-Ion Batteries

This paper deals with the safety devices incorporated in the most commercial 18650 lithium-ion (Li-ion) cells. The systems have been effective at cell level, but with the development of Li-ion cells in module or battery pack configurations, safety device breakdown occurs during battery operation. The 18650 cells include a current interrupt device (CID), which manages cell overcharge by opening the circuitry when an overpressure event occurs. But CID opening under high voltage can undergo electric arcs and it can lead to a thermal runaway in the most extreme cases. First, in this paper, the general risks that exist in batteries and the related protection technologies are reviewed. This review is completed by arcing tests by contact opening and an arc behavior analysis. This paper also analyzes the direct current electric arc risks and damages that can occur to the mechanical safety vent pressure of the cylindrical 18650 Li-ion batteries during CID opening. In addition, an assessment of the electric arc risks related to the battery system and at CID level is performed. This paper will shed light to the electric arc phenomena and reduce the arcing risk in Li-ion batteries. The proposed solutions are a step toward the arc risk mitigation.

Crash analysis of a conceptual electric vehicle with a damage tolerant battery pack

In current electric vehicles, batteries fulfill only the role of power source and are stored within the passenger cabin, protected from external impact loads. This study considers a multifunctional, damage tolerant battery system which combines the energetic material with mechanically sacrificing elements that control mechanical stresses and dissipate energy. With such a multifunctional battery system in place it is proposed to place the battery pack into the secondary safe zone of a unibody-type vehicle. Full-vehicle crash analyses via finite element simulations are conducted for several battery pack configurations, thereby comparing the multifunctional battery system to battery packs with batteries alone and battery packs where cellular solids are used as energy absorbers. The analysis demonstrates the use of a multifunctional (damage tolerant and energy storage capable) battery system to ensure battery safety and aid in the energy absorption in a crash overall. The use of the multifunctional battery systems can aid in solving technology limitations of electric vehicles.

Dynamic electrothermal battery pack modelling and simulation of pack imbalance

In this paper, we present a battery pack model and simulation methodology in order to study some of the operation characteristics of different battery pack configurations, under different temperatures, different initial state of charge (SoC), and different current profiles. During battery pack operation, there can exist significant pack imbalances caused by non-uniform temperature distributions, state of health differences, and manufacturing differences. To study the imbalance that occurs in a pack, we derive an efficient analytical dynamic battery single cell model with scheduled parameters that is used inside a larger pack model. Since the pack model is made up of individual battery cells, pack imbalances can be studied. It is shown that the battery pack model and simulation methodology developed may be extended to support any topology and pack sizing.

Personal Monitoring System for Measuring Environmental Tobacco Smoke Exposure

A monitoring system, calibration system and bar code-based, computer sample tracking system for measuring personal exposures to environmental tobacco smoke (ETS) are described. The monitoring system collects both vapor and particulate phase ETS analytes on a sorbent tube and filter, respectively, using a single sampling pump. Several battery pack configurations are described which enable continuous sampling times of 16, 28 and 48 h. Detailed methodologies are presented for determining nicotine, 3-ethenylpyridine and myosmine in the vapor phase and respirable suspended particles, solanesol, scopoletin, UVPM and FPM in the particulate phase. Experiments conducted in a controlled-environment test chamber show that all analytes increase linearly with the number of cigarettes smoked. In addition, 3-ethenylpyridine is shown to track closely the vapor phase of ETS (as measured by CO and FID) while nicotine poorly estimates the vapor phase. These data support previously published findings that 3-ethenylpyridine i...