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Pouch cells are increasingly popular form factors for the construction of energy storage systems in electric vehicles of all classes. Knowledge of the stress generated by these higher capacity pouch cells is critical to properly design battery modules and packs for both normal and abnormal operation. Existing literature predominantly offers data on smaller pouch cells with capacities of less than 10 Ah, leaving a gap in our understanding of the behavior of these larger cells. This experimental study aimed to bridge this knowledge gap by measuring loads and stresses in constrained 65 Ah pouch cells under both cycling and abuse conditions. To capture the desired responses, a load cell was located within a robust fixture to measure cell stress in real time after the application of a preload of approximately 30 kilograms or 294 N, equivalent to a pressure of 0.063 bar, with a fixed displacement.

The capacity of a lithium-ion battery decreases during cycling. This capacity loss or fade occurs due to several different mechanisms associated with unwanted side reactions that occur in these batteries. The same reactions occur during overcharge and cause electrolyte decomposition, passive film formation, active material dissolution, and other phenomena. As the battery ages the accuracy of state of charge prediction decreases and vulnerability to persistent overcharge increases. Moreover, as the battery ages, its tolerance to such unintended overcharge changes. This tolerance depends on the nature of the history of cycle and calendar aging. A map of this tolerance in the BMS can provide awareness of the factor of safety due to overcharge as battery ages. Signatures of early warning signs of incipient thermal runaway due to overcharge can also be very useful features in a BMS.

Future lunar missions will utilize a Lunar DC microgrid (LDCMG) to construct the infrastructure for distributing, storing, and utilizing electrical energy. The LDCMG’s energy management, of which energy storage systems (ESS) are crucial components, will be essential to the success of the missions. Standard system design currently employs a rule-of-thumb approach in which design methodologies rely on heuristics that may only evaluate local power balancing requirements. The Hamiltonian surface shaping and power flow control (HSSPFC) method can also be utilized to analyze and design the lunar LDCMG power distribution network and ESS. In this research, the HSSPFC method will be utilized to determine the ideal energy storage requirements for ESS and the optimally distributed control architecture.

Increasing regulatory demand to reduce CO2 emissions has led to an industry focus on electrified vehicles while limiting the development of conventional internal combustion engine (ICE) and hybrid powertrains. Hybrid electric vehicle (HEV) powertrains rely on conventional SI mode IC engines that are optimized for a narrow operating range. Advanced combustion strategies such as Gasoline Compression Ignition (GCI) have been demonstrated by several others including the authors to improve brake thermal efficiency compared to both gasoline SI and Diesel CI modes. Soot and NOx emissions are also reduced significantly by using gasoline instead of diesel in GCI engines due to differences in composition, fuel properties, and reactivity. In this work, an HEV system was proposed utilizing a multi-mode GCI based ICE combined with a HEV components (e-motor, battery, and invertor).

Extreme Fast Charging (XFC) infrastructure is crucial for an increase in electric vehicle (EV) adoption. However, an unmanaged implementation may lead to negative grid impacts and huge power costs. This paper presents an optimal energy management strategy to utilize grid-connected Energy Storage Systems (ESS) integrated with XFC stations to mitigate these grid impacts and peak demand charges. To achieve this goal, an algorithm that controls the charge and discharge of ESS based on an optimal power threshold is developed. The optimal power threshold is determined to carry out maximum peak shaving for given battery size and SOC constraints.

There is an ongoing proliferation of electric and electrified vehicles as manufacturers seek to reduce their carbon footprint and meet the carbon reduction targets mandated by governments around the world. An ongoing challenge in electric vehicle design is the efficient and safe design of battery packs. There are significant safety challenges for lithium battery packs relating to thermal runaway, which can be initiated through overheating and internal short from defects or external damage. This work proposes a robust method to couple the mechanical damage in a battery module calculated from a dynamic model with a thermal model of the battery that includes heating from electro-chemical sources as well as Arrhenius reactions from the battery cells. The authors identify the main sources of thermal runaway initiation and propagation in an impact scenario simulating a vehicle collision. The modeling approach was developed and validated using test data.

Overcharging lithium-ion batteries is a failure mode that is observed if the battery management system (BMS) or battery charger fails to stop the charging process as intended. Overcharging can easily lead to thermal runaway in a battery. In this paper, nickel manganese cobalt (NMC) battery modules from the Chevrolet Bolt, lithium manganese oxide (LMO) battery modules from the Chevrolet Volt, and lithium iron phosphate (LFP) battery modules from a hybrid transit bus were overcharged. The battery abuse and emissions tests were designed to intentionally drive the three different battery chemistries into thermal runaway while measuring battery temperatures, battery voltages, gaseous emissions, and feedback from volatile organic compound (VOC) sensors. Overcharging a battery can cause lithium plating and other exothermic reactions that will lead to thermal runaway.

The emerging need of building an efficient Electric Vehicle (EV) charging infrastructure requires the investigation of all aspects of Vehicle-Grid Integration (VGI), including the impact of EV charging on the grid, optimal EV charging control at scale, and communication interoperability. This paper presents a cloud-based simulation and testing platform for the development and Hardware-in-the-Loop (HIL) testing of VGI technologies. Although the HIL testing of a single charging station has been widely performed, the HIL testing of spatially distributed EV charging stations and communication interoperability is limited. To fill this gap, the presented platform is developed that consists of multiple subsystems: a real-time power system simulator (OPAL-RT), ISO 15118 EV Charge Scheduler System (EVCSS), and a Smart Energy Plaza (SEP) with various types of charging stations, solar panels, and energy storage systems.

Internal short-circuit in cells/batteries is a phenomenon where there is direct electrical contact between the positive and negative electrodes leading to thermal runaway. The nail penetration tests were used to simulate an internal short circuit within the battery, where a conductive nail was used to pierce the battery cell separator membrane which provided direct electrical contact between the positive and negative electrodes. The batteries tested during this work were common batteries used in existing automotive applications, and they included a nickel manganese cobalt (NMC) battery from a Chevrolet Bolt, a lithium manganese oxide (LMO) battery from a Chevrolet Volt, and a lithium iron phosphate (LFP) battery in a hybrid transit bus. The battery abuse and emissions tests were designed to intentionally drive the three different battery chemistries into thermal runaway while measuring battery temperatures, battery voltages and gaseous emissions.

Internal short-circuit in cells/batteries is a phenomenon where there is direct electrical contact between the positive and negative electrodes leading to thermal runaway. The nail penetration tests were used to simulate an internal short circuit within the battery, where a conductive nail was used to pierce the battery cell separator membrane which provided direct electrical contact between the positive and negative electrodes. The batteries tested during this work were common batteries used in existing automotive applications, and they included a nickel manganese cobalt (NMC) battery from a Chevrolet Bolt, a lithium manganese oxide (LMO) battery from a Chevrolet Volt, and a lithium iron phosphate (LFP) battery in a hybrid transit bus. The battery abuse and emissions tests were designed to intentionally drive the three different battery chemistries into thermal runaway while measuring battery temperatures, battery voltages and gaseous emissions.

The short-term future direction of the automotive transportation sector is uncertain. Many governments and environmental localities around the world are proposing internal combustion engine (ICE) bans and enacting large subsidy programs for zero-tailpipe emissions vehicles powered by batteries or fuel-cells. Such policies can be effective in driving the consumer towards specific powertrains. The reason for such aggressive change is to reduce the sector’s carbon footprint. However, it is not clear if these proposals will reduce greenhouse gas (GHG) emissions. Emissions from raw material extraction, manufacturing, and power generation are shadowed by the focus on reducing the reliance on fossil fuel use. Emissions from non-tailpipe sources should also be considered before pushing for a rapid change to powertrains. Life-cycle analysis (LCA) can assess the GHG emissions produced before, during and after the life of a vehicle in a cradle-to-grave analysis.

With the increasing level of electrification of on-road, off-road and stationary applications, use of larger lithium-ion battery packs has become essential. These packs require large capital investments on the order of millions of dollars and pose a significant risk of self-annihilation without rigorous safety evaluation and management. Testing these larger battery packs to validate design changes can be cost prohibitive. A reliable numerical simulation tool to predict battery thermal runaway under various abuse scenarios is essential to engineer safety into the battery pack design stage. A comprehensive testing & simulation workflow has been established to calibrate and validate the numerical modeling approach with the test data for each of the individual sub model - electrochemical, internal short circuit and thermal abuse model. A four-equation thermal abuse model was built and validated for lithium-ion 21700 form factor cylindrical cells using NCA cathodes.

Lithium plating refers to the phenomenon where lithium metal is deposited onto the surface of the anode instead of being intercalated into the carbon sites of the graphite. The lithium metal will cover a portion of the surface area of the anode, which blocks intercalation sites and increases charge gradients. Lithium plating most often occurs when charging the battery at low ambient temperatures or at a high current rate, but lithium plating formation has also been linked to solid electrolyte interface (SEI) growth towards the later stages of life. Lithium plating may significantly reduce a battery cell’s performance in terms of charge capacity, and if severe enough, the lithium metal may form a bridge across the separator of the cell, leading to short circuits and potential safety concerns. The internal research performed by Southwest Research Institute explored how to create a battery model to detect the formation of lithium plating in real time.

As advances in electrification continue within the vehicle industry, improving the front-end design process and managing the safety aspects of lithium-ion batteries is increasingly important. Structural damage to lithium-ion batteries can cause internal short circuit, leading to a large energy release that can lead to fire and thermal runaway that propagates throughout the battery pack. Southwest Research Institute has developed a mechanical model that can accurately predict mechanically-induced damage to lithium-ion battery cells and battery packs. This model also predicts whether the external damage will cause an internal short-circuit. This modeling process was illustrated using 21700 cylindrical cells with NCA cathode chemistry. High-speed impact tests were used to calibrate a single cell model, which was then scaled to a 12-cell battery module. This model was then used to accurately predict the outcome of an impact test on a 72-cell battery module.

Battery temperature variations have a strong effect on both battery aging and battery performance. Significant temperature variations will lead to different battery behaviors. This influences the performance of the Hybrid Electric Vehicle (HEV) energy management strategies. This paper investigates how variations in battery temperature will affect Lithium-ion battery aging and fuel economy of a HEV. The investigated energy management strategy used in this paper is the Equivalent Consumption Minimization Strategy (ECMS) which is a well-known energy management strategy for HEVs. The studied vehicle is a Honda Civic Hybrid and the studied battery, a BLS LiFePO4 3.2Volts 100Ah Electric Vehicle battery cell. Vehicle simulations were done with a validated vehicle model using multiple combinations of highway and city drive cycles. The battery temperature variation is studied with regards to outside air temperature.

Battery State of Charge (SOC) constraints are used to prevent the battery in Hybrid Electric Vehicles (HEVs) from over-charging or over-discharging. These constraints strongly influence the power-split of the HEV. This paper presents results on how Battery State of Charge (SOC) constraints effects Lithium ion battery aging and fuel economy when using the Equivalent Consumption Minimization Strategy (ECMS). The vehicle studied is the Honda Civic Hybrid. The battery used is A123 Systems’ ANR26650 battery cell. Vehicle simulation uses multiple combinations of highway and city drive cycles. For each combination of drive cycles, nine SOC constraints ranges are used. Battery aging is evaluated using a semi-empirical model combined with the accumulated Ah-throughput method which uses, as an input, the battery SOC trajectory from the vehicle simulations. The simulation results provide insight into how SOC constraints effect fuel economy as well as battery aging.

This paper considers optimal power management during the establishment of an expeditionary outpost using battery and vehicle assets for electrical generation. The first step in creating a new outpost is implementing the physical protection and barrier system. Afterwards, facilities that provide communications, fires, meals, and moral boosts are implemented that steadily increase the electrical load while dynamic events, such as patrols, can cause abrupt changes in the electrical load profile. Being able to create a fully functioning outpost within 72 hours is a typical objective where the electrical power generation starts with batteries, transitions to gasoline generators and is eventually replaced by diesel generators as the outpost matures. Vehicles with power export capability are an attractive supplement to this electrical power evolution since they are usually on site, would reduce the amount of material for outpost creation, and provide a modular approach to outpost build-up.

This paper studies the hardware-in-the-loop (HiL) design of a power-split hybrid electric vehicle (HEV) for the research of HEV lithiumion battery aging. In this paper, an electrochemical model of a lithium-ion battery pack with the characteristics of battery aging is built and integrated into the vehicle model of Autonomie® software from Argonne National Laboratory. The vehicle model, together with the electrochemical battery model, is designed to run in a dSPACE real-time simulator while the powertrain power distribution is managed by a dSPACE MicroAutoBoxII hardware controller. The control interface is designed using dSPACE ControlDesk to monitor the real-time simulation results. The HiL simulation results with the performance of vehicle dynamics and the thermal aging of the battery are presented and analyzed.

Vehicle-to-Grid (V2G) service has a potential to improve the reliability and stability of the electrical grid due to the ability of providing bi-directional power flow from/to the grid. However, frequent charging/discharging may impact the battery lifetime. This paper presents the analysis of battery degradation in three scenarios. In the first scenario, different battery capacities are considered. In the second scenario, the battery degradation with various depth of discharge (DOD) are studied. In the third scenario, the capacity loss due to different charging regime are compared. The charging/discharging of plug-in electric vehicles (PEVs) are simulated in a single-phase microgrid system integrated with a photovoltaics (PV) farm, an energy storage system (ESS), and ten electric vehicle service equipment (EVSE). The battery degradation model is an energy throughput model, which is developed based on the Arrhenius equation and a power law relationship between time and capacity fading.

A high voltage battery is an essential part of hybrid electric vehicles (HEVs). It is imperative to precisely estimate the state of charge (SOC) and state of health (SOH) of battery in real time to maintain reliable vehicle operating conditions. This paper presents a method of estimating SOC and SOH through the incorporation of current integration, voltage translation, and Ah-throughput. SOC estimation utilizing current integration is inadequate due to the accumulation of errors over the period of usage. Thus voltage translation of SOC is applied to rectify current integration method which improves the accuracy of estimation. Voltage translation data is obtained by subjecting the battery to hybrid pulse power characterization (HPPC) test. The Battery State of Health was determined by semi-empirical model combined with accumulated Ah-throughput method. Battery state of charge was employed as an input to estimate damages accumulated to battery aging through a real-time model.