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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.

According to the Annual Energy Outlook 2022 (AEO2022) report, almost 30% of the transport sector will still use internal combustion engines (ICE) until 2050. The transportation sector has been actively seeking different methods to reduce the CO2 emissions footprint of fossil fuels. The use of lower carbon-intensity fuels such as Renewable Diesel (RD) can enable a pathway to decarbonize the transport industry. This suggests the need for experimental or advanced numerical studies of RD to gain an understanding of its combustion and emissions performance. This work presents a numerical modeling approach to study the combustion and emissions of RD. The numerical model utilized the development of a reduced chemical kinetic mechanism for RD’s fuel chemistry. The final reduced mechanism for RD consists of 139 species and 721 reactions, which significantly shortened the computational time from using the detailed mechanism.

Simulation and testing are often done by different engineers in different departments of a company. This can lead to disconnects and unrealistic predictions, especially if the person doing simulations does not have an experimental background. On the other hand, experimental results can also include errors that result in misleading answers. It is important for the engineer doing either testing or simulation to have a good understanding for what results are plausible and what results might be suspect. This paper will provide examples where error crept into testing or simulation that could have been caught and corrected early if a good feel for “reasonable” results had been in place. The importance of understanding how a software package is analyzing the data will be explained, since settings buried deep within a menu structure can drive misleading results.

A physics-based spark ignition model was developed and integrated into a commercial CFD code. The model predicted the spark discharge process based on the electrical parameters of the secondary ignition circuit, tracked the spark motion as it was stretched by in-cylinder gas motion, and determined the resulting energy deposition to the gas. In concert with the existing kinetic solver in the CFD code, the resulting ignition and flame propagation processes were simulated. The model results have been validated against both imaging rig experiments of the spark in moving air and against engine experimental data. The model was able to replicate the key features of the spark and to capture the cyclic variability of high-dilution combustion when multiple engine cycles were simulated.

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.

Interaction between a diesel spray and piston plays a significant role in overall combustion and emissions performance in compression-ignition engines. It is essential to design the lip feature respective to spray targeting and the following charge motion for combustion systems that rely on spray-piston interaction strongly, such as a stepped-lip piston. This study used a numerical campaign using computational fluid dynamics (CFD) simulation to optimize a stepped-lip combustion system at a 22:1 compression ratio (CR) for both performance and emissions. This is a substantial step up in CR from the stock value of 17:1 for the same engine platform. A machine learning model was used to identify the best combination of features from a design space involving hundreds of potential piston designs and injector nozzle configurations. This study provides a discussion on the general combustion characteristics of the stepped-lip combustion system and the sensitivity of the design parameters.

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.

Selective Catalytic Reduction is the primary method of NOX emission abatement in lean-burn internal combustion. This process requires the decomposition of a 32.5 wt. % urea-water solution (UWS) to provide ammonia as a reducing agent for NOX, but at temperatures < 250 °C the injection of UWS is limited due to the formation of harmful deposits within an aftertreatment system and decreased ammonia production. Previous work has sufficiently demonstrated that the addition of surfactant and a urea/isocyanic acid (HNCO) decomposition catalyst to UWS can significantly decrease deposit formation within an aftertreatment system. The objective of this work was to further optimize the modified UWS formulation by investigating different types and concentrations of surfactants and titanium-based urea/HNCO catalyst. Because there is a correlation between surface tension and water evaporation, it was theorized that minimizing the surface tension of UWS would result in decreased deposit formation.

A comprehensive 3D Computational Fluid Dynamics (CFD) with conjugate heat transfer (CHT) tool was developed in-house for a Tesla Model 3 electric motor. To accurately predict the power loss (heat generation) inside the electric motor, the electromagnetic process was solved to obtain the spatial-dependent power loss in the rotor, stator, and windings. CFD was utilized for simulating the coolant oil flow using the multiphase Volume of Fluid (VOF) approach and Finite Element Analysis (FEA) was used for simulating the thermal process within the solid domains. These three separate analysis modules (electromagnetic, fluid flow and thermal solid) were coupled strongly to enable two-way interactions. Thermal results obtained from the final converged simulations were compared to the test data obtained from the thermocouple measurements for the two most representative operating points of this e-motor and showed reasonable predictions with similar trend as observed in the test.

Advanced diesel combustion systems continue to push the peak cylinder pressure limit of engines upward to allow high-efficiency combustion with high compression ratios (CR). The air-standard Otto and Diesel cycles indicate increased compression ratios lead to higher cycle efficiency. The study presented here describes the development and demonstration of a high-efficiency diesel combustion system. The study used both computational and experimental tools to develop the combustion system fully. Computational fluid dynamics (CFD) simulations were carried out to evaluate combustion with two combustion systems at a compression ratio of 22:1 with a Wave piston design (based on the production Volvo Wave piston). Analysis of combustion performance and emissions were performed to confirm the improvements these piston designs offered relative to the baseline combustion system for the engine. Companion single-cylinder engine (SCE) experiments were performed to validate the simulation results.

Water injection is an effective method for knock control in spark-ignition engines. However, the requirement of a separate water source and the cost and complexity associated with a fully integrated system creates a limitation of this method to be used in volume production engines. The engine exhaust typically contains 10-15% water vapor by volume which could be condensed and potentially stored for future use. In this study, the exhaust condensate composition was assessed for its use as an effective replacement for distilled water. Specifically, condensate samples were collected pre and post-three-way catalyst (TWC) and analyzed for acidity and composition. The composition of the pre and post-TWC condensates was found to be similar however, the pre-TWC condensate was mildly acidic. The mild acidity has the potential to corrode certain components in the intake air circuit.

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.

A computational fluid dynamics (CFD) model was developed to explore gasoline compression ignition (GCI) combustion. Results were validated with single-cylinder engine (SCE) experiments. It was shown that the CFD model captured experimental results well. Cylinder pressure, heat release and emissions from the CFD model were also used to analyze the performance of GCI combustion with a current heavy-duty diesel engine platform. This work also provides detailed analysis on in-cylinder combustion and emissions using CFD. It was found that multiple injection strategy can deliver desirable fuel stratification profile that benefits both engine and emissions performance. A wave contoured piston was compared with a stepped-lip type piston for both GCI and Diesel combustion scenarios on the same engine platform. Stepped-lip pistons offer an opportunity to use multiple injection strategies to overcome high UHC emissions of GCI combustion when compared to wave pistons.

The Exhaust Composition Transient Operation LaboratoryTM (ECTO-LabTM) is a burner system developed at Southwest Research Institute (SwRI) for simulation of IC engine exhaust. The current system design requires metering and combustion of nitromethane in conjunction with the primary fuel source as the means of NOX generation. While this method affords highly tunable NOX concentrations even over transient cycles, no method is currently in place for dictating the speciation of nitric oxide (NO) and nitrogen dioxide (NO2) that constitute the NOX mixture. NOX generated through combustion of nitromethane is dominated by NO, and generally results in an NO2:NOX ratio of < 5 %. Generation of any appreciable quantities of NO2 is therefore dependent on an oxidation catalyst to oxidize a fraction of the NO to NO2.

Onboard sensing and external connectivity using Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I) and Vehicle-to-Everything (V2X) technologies allows a vehicle to "know" its future operating environment with some degree of certainty, greatly narrowing prior information gaps. The increased development of such connected and automated vehicle systems, currently used mostly for safety and driver convenience, presents new opportunities to improve the energy efficiency of individual vehicles [1, 2, 3, 4, 5]. Southwest Research Institute (SwRI) in collaboration with Toyota Motor North America and University of Michigan is currently working on improving energy consumption of a Toyota Prius Prime 2017 by 20%. This paper will provide an overview of the various algorithms that are being developed to achieve the energy consumption target. Custom tools such as a traffic simulator was built to model traffic flow in Fort Worth, Texas with sufficient accuracy.

The process of developing, parameterizing, validating, and maintaining models occurs within a wide variety of tools, and requires significant time and resources. To maximize model utilization, models are often shared between various toolsets and experts. Model integration is typically divided into two categories: model exchange and model co-simulation. Of these two categories, model co-simulation is typically regarded as the more complex and difficult to implement. Co-Simulation provides the ability to integrate models between different toolsets or incompatible versions of the same software. Additionally, it provides the capabilities for real-time simulations and hardware-in-the-loop test scenarios. This paper reviews some of the common co-simulation data communication methods including pipes and file input/output. The differences between serial and parallel, aka synchronous and asynchronous, communication patterns are also discussed.

Present day natural gas engines have a significant efficiency disadvantage but benefit with low carbon-dioxide emissions and cheap three-way catalysis aftertreatment. The aim of this work is to improve the efficiency of a natural gas engine on par with a diesel engine. A Cummins-Westport ISX12-G (diesel) engine is used for the study. A baseline model is validated in three-dimensional Computational Fluid Dynamics (CFD). The challenge of this project is adapting the diesel engine for the natural gas fuel, so that the increased squish area of the diesel engine piston can be used to accomplish faster natural gas burn rates. A further increase efficiency is achieved by switching to D-EGR technology. D-EGR is a concept where one or more cylinders are run with excess fueling and its exhaust stream, containing H2 and CO, is cooled and fed into the intake stream. With D-EGR although there is an in-cylinder presence of a reactive H2-CO reformate, there is also higher levels of dilution.

The abnormal autoignition of the unburned gas, namely knock, at high loads is a major challenge for modern spark ignited engines. Knock prevents the application of high compression ratios due to the increased unburned gas temperature, and it becomes increasingly severe for downsized engines with high specific powers. The current paper reports on the potential of utilizing continuously variable valve actuation (VVA) and low-pressure exhaust gas recirculation (EGR) to reduce knock tendency at high loads. Five speed / load points were investigated on a 1.6 L turbocharged gasoline direct injection engine. The brake specific fuel consumption (BSFC) response to the valve phasing and the intake valve lift was investigated with the design of experiment (DoE) approach. The DoE was conducted using a Box-Behnken surface response model. The results exhibited insensitive response of BSFC to intake valve lift and overlap.

A new generation of vehicle dynamics and powertrain control technologies are being developed to leverage information streams enabled via vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) connectivity [1, 2, 3, 4, 5]. While algorithms that use these connected information streams to enable improvements in energy efficiency are being studied in detail, methodologies to quantify and analyze these improvements on a vehicle have not yet been explored fully. A procedure to test and accurately measure energy-consumption benefits of a connected and automated vehicle (CAV) is presented. The first part of the test methodology enables testing in a controlled environment. A traffic simulator is built to model traffic flow in Fort Worth, Texas with sufficient accuracy. The benefits of a traffic simulator are two-fold: (1) generation of repeatable traffic scenarios and (2) evaluation of the robustness of control algorithms by introducing disturbances.