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Engine and aftertreatment solutions have been identified to meet the upcoming ultra-low NOX regulations on heavy duty vehicles in the United States and Europe. These standards will require changes to current conventional aftertreatment systems for dealing with low exhaust temperature scenarios while increasing the useful life of the engine and aftertreatment system. Previous studies have shown feasibility of meeting the US EPA and California Air Resource Board (CARB) requirements. This work includes a 15L diesel engine equipped with cylinder deactivation (CDA) and an aftertreatment system that was fully DAAAC aged to 800,000 miles. The aftertreatment system includes an e-heater (electric heater), light-off Selective Catalytic Reduction (LO-SCR) followed by a primary aftertreatment system containing a DPF and 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.

With the capability of avoiding failure in advance, failure prediction model is important not only to end users, but also to the service engineers in vehicle industry. This paper proposes an approach based on anomaly detection algorithms and telematic data to predict the failure of the engine air system with Turbo charger. Firstly, the relationship between air system and all obtained features are analyzed by both physical mechanism and data-wise. Then, the features including altitude, air temperature, engine output power, and charger pressure are selected as the input of the model, with the sampling interval of 1 minute. Based on the selected features, the healthy state for each vehicle is defined by the model as benchmark. Finally, the ‘Medium surface’ is determined for specific vehicle, which is a hyperplane with the medium points of the healthy state located at, to detect the minor weakness symptom (sub-health state).

Hydrogen Internal Combustion Engines (H2 ICE) are gaining recognition as a nearly emission-free alternative to traditional ICE engines. However, H2 ICE systems face challenges related to thermal management, N2O emissions, and reduced SCR efficiency in high humidity conditions (15% H2O). This study assesses how hydrogen in the exhaust affects after-treatment system components for H2 ICE engines, such as Selective Catalytic Reduction (SCR), Hydrogen Oxidation Catalyst (HOC), and Ammonia Slip Catalyst (ASC). Steady-state experiments with inlet H2 inlet concentrations of 0.25% to 1% and gas stream moisture levels of up to 15% H2O were conducted to characterize the catalyst response to H2 ICE exhaust. The data was used to calibrate and validate system component models, forming the basis for a system simulation.

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.

Since the early 1990’s, commercial vehicles have suffered from repeated vulnerability exploitations that resulted in a need for improved automotive cybersecurity. This paper outlines the strategies and challenges of implementing an automotive Zero Trust Architecture (ZTA) to secure intra-vehicle networks. Zero Trust (ZT) originated as an Information Technology (IT) principle of “never trust, always verify”; it is the concept that a network must never assume assets can be trusted regardless of their ownership or network location. This research focused on drastically improving security of the cyber-physical vehicle network, with minimal performance impact measured as timing, bandwidth, and processing power. The automotive ZTA was tested using a software-in-the-loop vehicle simulation paired with resource constrained hardware that closely emulated a production vehicle network.

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.

Upcoming regulations from CARB and EPA will require diesel engine manufacturers to validate aftertreatment durability with full useful life aged components. To this end, the Diesel Aftertreatment Accelerated Aging Cycle (DAAAC) protocol was developed to accelerate aftertreatment aging by accounting for hydrothermal aging, sulfur, and oil poisoning deterioration mechanisms. Two aftertreatment systems aged with the DAAAC protocol, one on an engine and the other on a burner system, were directly compared to a reference system that was aged to full useful life using conventional service accumulation. After on-engine emission testing of the fully aged components, DOC and SCR catalyst samples were extracted from the aftertreatment systems to compare the elemental distribution of contaminants between systems. In addition, benchtop reactor testing was conducted to measure differences in catalyst performance.

Shafaat and Kenley in 2015 identified the opportunity to improve System Engineering Standards by incorporating the design principle of learning. The System Level Assessment (SLA) Methodology is an approach that fulfills this need by efficiently capturing the learnings of a team of subject matter experts in the early stages of product system design. By gathering expertise, design considerations are identified that when used with market and business requirements improve the overall quality of the product system. To evaluate the effectiveness of this approach, the methodology has been successfully applied over 400 times within each realm of the New Product Introduction process, including most recently to a Technology Development program (in the earliest stages of the design process) to assess the viability of various electrification technologies under consideration by an automotive Tier 1 supplier.

This work is a part of medium-duty Low NOx technology development project with a focus on evaluating a combination of engine and advanced aftertreatment for 0.02 g/bhp-hr NOx regulation proposed by CARB (California air resource board). In this project, a control oriented chemical kinetics model of SCR (Selective catalytic reduction) was used in the aftertreatment controller that is susceptible to performance degradation due to hydrothermal and chemical aging. This paper focuses on modeling the NOx conversion and NH3 storage characteristics using a controls oriented SCR plant model which is further used for a model-based urea dosing scheme. A set of steady state reactor tests were used to calibrate the SCR performance at degreened, hydrothermal only and hydrothermal + chemical aging conditions and also to determine inhibition factors related to aging. The resultant model is capable of simulating SCR performance deterioration such as a reduction in NOx conversion and NH3 storage.

This program involved the detailed evaluation of a novel laser-based in-exhaust ammonia sensor using a diesel fuel-based burner platform integrated with an ammonia injection system. Test matrix included both steady-state modes and transient operation of the burner platform. Steady-state performance evaluation included tests that examined impact of exhaust gas temperature, gas velocity and ammonia levels on sensor response. Furthermore, cross sensitivity of the sensor was examined at different levels of NOX and water vapor. Transient tests included simulation of the FTP test cycles at different ammonia and NOX levels. A Fourier transform infrared (FTIR) spectrometer as well as NIST traceable ammonia gas bottles (introduced into the exhaust stream via a calibrated flow controller) served as references for ammonia measurement.

Diesel oxidation catalyst (DOC) is one of the critical catalyst components in modern diesel aftertreatment systems. It mainly converts unburned hydrocarbon (HC) and CO to CO2 and H2O before they are released to the environment. In addition, it also oxidizes a portion of NO to NO2, which improves the NOx conversion efficiency via fast SCR over the downstream selective catalytic reduction (SCR) catalyst. HC light-off tests, with or without the presence of NOx, has been typically used for DOC evaluation in laboratory. In this work, we aim to understand the influences of DOC light-off experimental conditions, such as initial temperature, initial holding time, HC species, with or without the presence of NOx, on the DOC HC light-off behavior. The results indicate that light-off test with lower initial temperature and longer initial holding time (at its initial temperature) leads to higher DOC light-off temperature.

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).

In 2020, CARB adopted the low NOX omnibus ruling, which provided revisions to on-road heavy duty engine compliance standards and certification practices. As part of the updates to the regulation, CARB has introduced a new in-use vehicle testing process that broadens the operation modes tested and considers the manufacturer’s intended vehicle application. Compared to the previous method, or the Not-to-Exceed approach, cold start and low ambient temperature provisions were included as part of the updates. The inclusion of low temperature operation requires the OEMs to design a robust engine and aftertreatment package that extends NOX conversion performance. The following work discusses the NOX emissions performance impact in a low temperature ambient environment. The engine and aftertreatment system evaluated was designed to comply with CARB’s low NOX regulations. The cycles tested included the CARB Southern NTE cycle and an FTP-LLC protocol.

Typical two-site storage-based SCR plant models in literature consider NH3 stored in the first site to participate in NH3 storage, NOx conversion and second site to only participate in NH3 storage passively. This paper focuses on quantifying the impact of stored NH3 in the second site on the overall NOx conversion for an ultra-low NOx system due to intra site NH3 mass transfer. Accounting for this intra site mass transfer leads to better prediction of SCR out NH3 thus ensuring compliance with NH3 coverage targets and improved dosing characteristics of the controller that is critical to achieving ultra-low NOx standard. The stored NH3 in the second site undergoes mass transfer to the first site during temperature ramps encountered in a transient cycle that leads to increased NOx conversion in conditions where the dosing is switched off. The resultant NH3 coverage fraction prediction is critical in dosing control of SCR.

Aftertreatment durability demonstration is a required validation exercise for on-road medium and heavy-duty diesel engine certification. The demonstration is meant to validate emissions compliance for the engine and aftertreatment system at full useful life or FUL. Current certification practices allow engine manufacturers to complete partial aging and then extrapolate emissions performance results to FUL. While this process reduces the amount of service accumulation time, it does not consider changes in the aftertreatment deterioration rate. Rather, deterioration is assumed to occur at a linear rate, which may lead to false conclusions relating to emissions compliance. With CARB and EPA’s commitment to the reduction of criteria emissions, emphasis has also been placed on revising the existing certification practices. The updated practices would require engine manufacturers to certify with an aftertreatment system aged to FUL.

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.

Southwest Research Institute (SwRI) utilizes the burner-based Exhaust Composition Transient Operation LaboratoryTM (ECTO-Lab) to accurately simulate transient engines and replicate real exhaust that is produced by light and heavy-duty engines for aftertreatment aging and evaluations. This system can generate and dose NOX over transient cycles from a range of 20 ppm to 1200 ppm where the NOX is generated by the in-situ decomposition and combustion of a fuel-bound, nitrogen containing compound. During the combustion and decomposition of the nitrogen containing compound over 95 % of the NOX generated is in the form of NO. To authentically simulate exhaust gases, it is necessary to account for the distribution of the NO to the NO2. Since previous work has established that the decomposition of nitric acid can be utilized as a method to generate NO2, the objective of this project was to develop control of NO and NO2 within SwRI’s ECTO-Lab through the decomposition of nitric acid.