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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.

Vehicle-to-everything (V2X) communication, primarily designed for communication between vehicles and other entities for safety applications, is now being studied for its potential to improve vehicle energy efficiency. In previous work, a 20% reduction in energy consumption was demonstrated on a 2017 Prius Prime using V2X-enabled algorithms. A subsequent phase of the work is targeting an ambitious 30% reduction in energy consumption compared to a baseline. In this paper, we present the Eco-routing algorithm, which is key to achieving these savings. The algorithm identifies the most energy-efficient route between an Origin-Destination (O-D) pair by leveraging information accessible through commercially available Application Programming Interfaces (APIs). This algorithm is evaluated both virtually and experimentally through simulations and dynamometer tests, respectively, and is shown to reduce vehicle energy consumption by 10-15% compared to the baseline over real-world routes.

As GHG and fuel economy regulations of light-duty vehicles have become more stringent, advanced emissions reduction technology has extensively penetrated the US light-duty vehicle fleet. This new technology includes not only advanced conventional engines and transmissions, but also greater adoption of electrified powertrains. In 2022, electrified vehicles – including mild hybrids, strong hybrids, plug-ins, and battery electric vehicles – made up nearly 17% of the US fleet and are on track to further increase their proportion in subsequent years. The Environmental Protection Agency (EPA) has previously used its Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) full vehicle simulation tool to evaluate the greenhouse gas (GHG) emissions of light-duty vehicles. ALPHA contains a library of benchmarked powertrain components that can be matched to specific vehicles to explore GHG emissions performance.

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.

Trained human raters have been used by organizations such as the Coordinating Research Council (CRC) to assess the vehicle driveability performance effect of fuel volatility. CRC conducts workshops to test fuel effects and their impact on vehicle driveability. CRC commissioned Southwest Research Institute (SwRI) to develop a “Trick Car” vehicle that could trigger malfunctions on-demand that mimic driveability events. This vehicle has been used to train novice personnel on the CRC Driveability Procedure E-28-94. While largely effective, even well-trained human raters can be inconsistent with other raters. Further, CRC rater workshop programs used to train and calibrate raters are infrequent, and there are a limited number of available trained raters. The goal of this program was to augment or substitute human raters with an electronic driveability sensing system.

Eco-driving algorithms enabled by Vehicle to Everything (V2X) communications in Connected and Automated Vehicles (CAVs) can improve fuel economy by generating an energy-efficient velocity trajectory for vehicles to follow in real time. Southwest Research Institute (SwRI) demonstrated a 7% reduction in energy consumption for fully loaded class 8 trucks using SwRI’s eco-driving algorithms. However, the impact of these schemes on vehicle emissions is not well understood. This paper details the effort of using data from SwRI’s on-road vehicle tests to measure and evaluate how eco-driving could impact emissions. Two engine and aftertreatment configurations were evaluated: a production system that meets current NOX standards and a system with advanced aftertreatment and engine technologies designed to meet low NOX 2031+ emissions standards.

Despite considerable progress towards clean air in previous decades, parts of the United States continue to struggle with the challenge of meeting the ambient air quality targets for smog-forming ozone mandated by the U.S. EPA, with some of the most significant challenges being seen in California. These continuing issues have highlighted the need for further reductions in emissions of NOX, which is a precursor for ozone formation, from a number of key sectors including the commercial vehicle sector. In response, the California Air Resources Board (CARB) embarked on a regulatory effort culminating in the adoption of the California Heavy-Duty Low NOX Omnibus regulation.[1] This regulatory effort was supported by a series of technical programs conducted at Southwest Research Institute (SwRI).

Eco-Driving with connected and automated vehicles has shown potential to reduce energy consumption of an individual (i.e., ego) vehicle by up to 15%. In a project funded by ARPA-E, a team led by Southwest Research Institute demonstrated an 8-12% reduction in energy consumption on a 2017 Prius Prime. This was demonstrated in simulation as well as chassis dynamometer testing. The authors presented a simulation study that demonstrated corridor-level energy consumption improvements by about 15%. This study was performed by modeling a six-kilometer-long urban corridor in Columbus, Ohio for traffic simulations. Five powertrain models consisting of two battery electric vehicles (BEVs), a hybrid electric vehicle (HEV), and two internal combustion engine (ICE) powered vehicles were developed. The design of experiment consisted of sweeps for various levels of traffic, penetration of smart vehicles, penetration of technology, and powertrain electrification.

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.

Vehicle to Everything (V2X) communication has enabled on-board access to information from other vehicles and infrastructure. This information, traditionally used for safety applications, is increasingly being used for improving vehicle fuel economy [1-5]. This work aims to demonstrate energy consumption reductions in heavy/medium duty vehicles using an eco-driving algorithm. The algorithm is enabled by V2X communication and uses data contained in Basic Safety Messages (BSMs) and Signal Phase and Timing (SPaT) to generate an energy-efficient velocity trajectory for the vehicle to follow. An urban corridor was modeled in a microscopic traffic simulation package and was calibrated to match real-world traffic conditions. A nominal reduction of 7% in energy consumption and 6% in trip time was observed in simulations of eco-driving trucks.

Numerous studies have demonstrated significant energy reduction for an ego vehicle by up to 20% leveraging Vehicle-to-Everything (V2X) technologies [1-4]. Some studies have also analyzed the impact of such vehicles on the energy consumption of other vehicles in a suburban or a highway corridor [5, 6], but the impact in an urban setting has not been studied yet. Southwest Research Institute (SwRI), in collaboration with Continental and Hyundai, is currently working on a Department of Energy funded project that is focused on quantifying the impact of multiple ego vehicles (smart vehicles) on the total energy consumption of the corridor under various traffic conditions, vehicle electrification level, vehicle-to-vehicle (V2V) technology penetration, and the number of smart (ego) vehicles in an urban setting. A six-kilometer-long urban corridor from Columbus, Ohio was modeled and calibrated with real-world data in PTV Vissim traffic microsimulation software.

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.

In this work, a dynamically loaded hydrodynamic journal bearing test rig is developed and introduced. The rig is a novel design, using a hydraulic actuator with fast acting spool valves to apply load to a connecting rod. This force is transmitted through the connecting rod to the large end bearing which is mounted on a spinning shaft. The hydraulic actuator allows for fully variable control and can be used to apply either static load in compression or tension, or dynamic loading to simulate engine operation. A variable speed electric motor controls shaft speed and is synchronized to the hydraulic actuator to accurately simulate loading to represent all four engine strokes. A high precision torque meter enables direct measurements of friction torque, while shaft position is measured via a high precision encoder.

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.

With the advancement of engine technologies and combustion strategies, aftertreatment architectures are expected to evolve as they continue to be the primary emissions mitigation hardware. Some of the engine approaches offer unique challenges and benefits that are not well understood beyond criteria pollutant emissions. As such, there continues to be a need to quantify engine emissions characteristics in pursuit of catalyst technology development and the use of advanced simulation tools. The following study discusses results from an extensive engine emissions assessment for current state-of-the-art technology and novel combustion regimes. The engines tested include a Tier 4 final compliant 6.8 L John Deere PSS 6068 diesel engine, a modified 15 L diesel engine, and a dual fuel 13 L natural gas-diesel engine. The dual fuel engine could operate in conventional positive ignition mode (CDF) or low temperature reactivity-controlled compression ignition mode (RCCI).

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.