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The Particle Number–Portable Emission Measurement System (PN-PEMS) came into force with Euro VI Phase E regulations starting January 1, 2022. However, positive ignition (PI) engines must comply from January 1, 2024. The delay was due to the unavailability of the PN-PEMS system that could withstand high concentrations of water typically present in the tailpipe (TP) of CNG vehicles, which was detrimental to the PN-PEMS systems. Thus, this study was designed to evaluate the condensation particle counter (CPC)-based PN-PEMS measurement capabilities that was upgraded to endure high concentration of water. The PN-PEMS measurement of solid particle number (SPN23) greater than 23 nm was compared against the laboratory-grade PN systems in four phases. Each phase differs based upon the PN-PEMS and PN system location and measurements were made from three different CNG engines. In the first phase, systems measured the diluted exhaust through constant volume sampler (CVS) tunnel.

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 National Highway Traffic Safety Administration (NHTSA) plays a crucial role in guiding the formulation of Corporate Average Fuel Economy (CAFE) standards, and at the forefront of this regulatory process stands Argonne National Laboratory (Argonne). Argonne, a U.S. Department of Energy (DOE) research institution, has developed Autonomie—an advanced and comprehensive full-vehicle simulation tool that has solidified its status as an industry standard for evaluating vehicle performance, energy consumption, and the effectiveness of various technologies. Under the purview of an Inter-Agency Agreement (IAA), the DOE Argonne Site Office (ASO) and Argonne have assumed the responsibility of conducting full-vehicle simulations to support NHTSA's CAFE rulemaking initiatives. This paper introduces an innovative approach that hinges on a large-scale simulation process, encompassing standard regulatory driving cycles tailored to various vehicle classes and spanning diverse timeframes.

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.

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.

Over the past couple of years, Argonne National Laboratory has tested, analyzed, and validated automobile models for the light duty vehicle class, including several types of powertrains including conventional, hybrid electric, plug-in hybrid electric and battery electric vehicles. Argonne’s previous works focused on the light duty vehicle models, but no work has been done on medium and heavy-duty vehicles. This study focuses on the validation of shifting control in advanced automatic transmission technologies for medium duty vehicles by using Argonne’s model-based high-fidelity, forward-looking, vehicle simulation tool, Autonomie. Different medium duty vehicles, from Argonne’s own fleet, including the Ram 2500, Ford F-250 and Ford F-350, were tested with the equipment for OBD (on-board diagnostics) signal data record. For the medium duty vehicles, a workflow process was used to import test data.

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.

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).

This paper presents the energy savings of an automated driving control applied to an electric vehicle based on the on-track testing results. The control is a universal speed planner that analytically solves the eco-driving optimal control problem, within a receding horizon framework and coupled with trajectory tracking lower-level controls. The automated eco-driving control can take advantage of signal phase and timing (SPaT) provided by approaching traffic lights via vehicle-to-infrastructure (V2I) communications. At each time step, the controller calculates the accelerator and brake pedal position (APP/BPP) based on the current state of the vehicle and the current and future information about the surrounding environment (e.g., speed limits, traffic light phase).

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.

The US Department of Energy’s Co-Optimization of Engine and Fuels Initiative (Co-Optima) investigated how unique properties of bio-blendstocks considered within Co-Optima help address emissions challenges with mixing controlled compression ignition (i.e., conventional diesel combustion) and enable advanced compression ignition modes suitable for implementation in a diesel engine. Additionally, the potential synergies of these Co-Optima technologies in hybrid vehicle applications in the medium- and heavy-duty sector was also investigated. In this work, vehicles system were simulated using the Autonomie software tool for quantifying the benefits of Co-Optima engine technologies for medium-duty trucks. A Class 6 delivery truck with a 6.7 L diesel engine was used for simulations over representative real-world and certification drive cycles with four different powertrains to investigate fuel economy, criteria emissions, and performance.

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.

This paper describes a configuration and controller, designed using Autonomie,1 for dual-motor battery electric vehicle (BEV) heavy-duty trucks. Based on the literature and current market research, this model was designed with two electric motors, one on the front axle and the other on the rear axle. A rule-based control algorithm was designed for the new dual-motor BEV, based on the model, and the control parameters were optimized by using a genetic algorithm (GA). The model was simulated in diverse driving cycles and gradeability tests. The results show both a good following of the desired cycle and achievement of truck gradeability performance requirements. The simulation results were compared with those of a single-motor BEV and showed reduced energy consumption with the high-efficiency operation of the two motors.

Improvements in vehicle technology impact the purchase price of a vehicle and its operating cost. In this study, the monetary benefit of a technology improvement includes the potential reduction in vehicle price from using cheaper or smaller components, as well as the discounted value of the fuel cost savings. As technology progresses over time, the value and benefit of improving technology varies as well. In this study, the value of improving a few selected technologies (battery energy density, electric drive efficiency, tire rolling resistance, aerodynamics, light weighting) is studied and the value of the associated cost saving is quantified. The change in saving as a function of time, powertrain selection and vehicle type is also quantified. For example, a 10% reduction in aerodynamic losses is worth $24,222 today but only $8,810 in 2030 in an electric long haul truck. The decrease in value is primarily due to expected battery cost reduction over time.

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.

The commercial vehicle industry continues to move in the direction of improving brake thermal efficiency while meeting more stringent diesel engine emission requirements. This study focused on demonstrating future emissions by using an exhaust burner upstream of a conventional aftertreatment system. This work highlights system results over the low load cycle (LLC) and many other pertinent cycles (Beverage Cycle, and Stay Hot Cycle, New York Bus Cycle). These efforts complement previous works showing system performance over the Heavy-Duty FTP and World Harmonized Transient Cycle (WHTC). The exhaust burner is used to raise and maintain the Selective Catalytic Reduction (SCR) catalyst at its optimal temperature over these cycles for efficient NOX reduction. This work showed that tailpipe NOX is significantly improved over these cycles with the exhaust burner.

The size and distribution of a vehicle’s tailpipe particulate emissions can have a strong impact on human health, especially if the particles are small enough to enter the human respiratory system. Gasoline direct injection (GDI) has been adopted widely to meet stringent fuel economy and CO2 regulations across the globe for recent engine architectures. However, the introduction of GDI has led to challenges concerning the particulate matter (PM) and particle number (PN) emissions from such engines. This study aimed to compare the particulate emissions of three SI combustion strategies: conventional SI, conventional stoichiometric low-pressure exhaust gas recirculation (LP-EGR), and Dedicated-EGR (D-EGR) at four specific test conditions. It was shown that the engine-out PM/PN for both the EGR strategies was lower than the conventional SI combustion under normal operating conditions. The test conditions were chosen to represent the WLTC test conditions.

Commercial vehicles require fast aftertreatment heat-up in order to move the SCR catalyst into the most efficient temperature range to meet upcoming NOX regulations. Today’s diesel aftertreatment systems require on the order of 10 minutes to heat up during a cold FTP cycle. The focus of this paper is to heat up the aftertreatment system as quickly as possible during cold starts and maintain a high temperature during low load, while minimizing fuel consumption. A system solution is demonstrated using a heavy-duty diesel engine with an end-of-life aged aftertreatment system targeted for 2027 emission levels using various levels of controls. The baseline layer of controls includes cylinder deactivation to raise the exhaust temperature more than 100° C in combination with elevated idle speed to increase the mass flowrate through the aftertreatment system. The combination yields higher exhaust enthalpy through the aftertreatment system.