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In this study, engine-out gaseous emissions are reviewed using the Fourier Transform Infrared (FTIR) spectroscopy measurement of methanol diesel dual fuel combustion experiments performed in a heavy-duty diesel engine. Comparison to the baseline diesel-only condition shows that methanol-diesel dual fuel combustion leads to higher regulated carbon monoxide (CO) emissions and unburned hydrocarbons (UHC). However, NOX emissions were reduced effectively with increasing methanol substitution rate (MSR). Under dual-fuel operation with methanol, emissions of nitrogen oxides (NOX), including nitric oxide (NO), nitrogen dioxide (NO2), and nitrous oxide (N2O), indicate the potential to reduce the burden of NOX on diesel after-treatment devices such as selective catalytic reduction (SCR).

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.

Multiple areas in the U.S. continue to struggle with achieving National Ambient Air Quality Standards for ozone. These continued issues highlight the need for further reductions in NOX emission standards in multiple industry sectors, with heavy-duty on-highway engines being one of the most important areas to be addressed. Starting in 2014, CARB initiated a series of technical demonstration programs aimed at examining the feasibility of achieving up to a 90% reduction in tailpipe NOX, while at the same time maintaining a path towards GHG reductions that will be required as part of the Heavy-Duty Phase 2 GHG program. These programs culminated in the Stage 3 Low NOX program, which demonstrated low NOX emissions while maintaining GHG emissions at levels comparable to the baseline engine.

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.

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.

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.

As governmental agencies focus on low levels of the oxides of nitrogen (NOx) emissions compliance, new off-road applications are being reviewed for both regulated and unregulated emissions to understand the technological challenges and requirements for improved emissions performance. The California Air Resources Board (CARB) has declared its intention to pursue more stringent NOX standards for the off-road market. As part of this effort, CARB initiated a program to provide a detailed characterization of emissions meeting the current Tier 4 off-road standards [1]. This work focused on understanding the off-road market, establishing a current technology emissions baseline, and performing initial modeling on potential low NOx solutions. This paper discusses a part of this effort, focuses on the emissions characterization from two non-road engine platforms, and compares the emissions species from different approaches designed to meet Tier 4 emissions regulations.

As agencies continue to focus on emissions compliance, low NOX discussions have started to propagate beyond the on-highway market. Nonroad applications, which contribute to 29% of the PM emissions and 11% of the NOX emissions in California, are being reviewed to understand the technological challenges and requirements for improved emissions performance. To help facilitate a nonroad low NOX technology demonstration, information from current engine and aftertreatment technologies required a detailed assessment. The following work will discuss the emissions characterization results from two non-road engine platforms. The intention of this study was to compare the emissions species from different approaches designed to meet Tier 4 emissions regulations. The platforms reflect available technology for DPF and non-DPF aftertreatment architectures.

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.

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 push for more stringent emissions regulations has resulted in larger, increasingly complex aftertreatment solutions. In particular, oxides of nitrogen (NOX) and particulate matter (PM) have been controlled using two separate systems, selective catalytic reduction (SCR) and the catalyze diesel particulate filter (CDPF), or the functionality has been combined into a single device producing the SCR on filter (SCRoF). The SCRoF forgoes beneficial NO2 production present in the CDPF to avoid NH3 oxidation which occurs when using platinum group metals (PGM) for oxidation. In this study, mixed-metal oxides are shown to oxidize NO to NO2 without appreciable NH3 oxidation. This selectivity leads to enhanced performance when combined with a typical Cu-zeolite catalyst.

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.