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The US EPA and the California Air Resources Board (CARB) require electric vehicle range to be determined according to the Society of Automotive Engineers (SAE) surface vehicle recommended practice J1634 - Battery Electric Vehicle Energy Consumption and Range Test Procedure. In the 2021 revision of the SAE J1634, the Short Multi-Cycle Test (SMCT) was introduced. The proposed testing protocol eases the chassis dynamometer test burden by performing a 2.1-hour drive cycle on the dynamometer, followed by discharging the remaining battery energy into a battery cycler to determine the Useable Battery Energy (UBE). Opting for a cycler-based discharge is financially advantageous due to the extended operating time required to fully deplete a 70-100kWh battery commonly found in Battery Electric Vehicles (BEVs).

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.

As part of the U.S. Environmental Protection Agency’s (EPA’s) continuing assessment of advanced light-duty automotive technologies in support of regulatory and compliance programs, a development project was started to study various test methods to benchmark Electric Drive Units (EDUs) consisting of an electric motor, inverter and a speed-reduction gearset. Several test methods were identified for consideration, including both in-vehicle testing of the complete EDU and stand-alone testing of the EDU and its subcomponents after removal from the vehicle. In all test methods explored, sweeps of speed and torque test points were conducted while collecting key EDU data required to determine efficiency, including motor torque and speed, direct current (DC) battery voltage and current into the inverter, and three-phase alternating current (AC) phase voltages and currents out of the inverter and into the electric motor.

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.

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.

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.

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.

This project’s objective was to generate experimental data to evaluate the impact of metals doped B20 on diesel particle filter (DPF) ash loading and performance compared to that of conventional petrodiesel. The effect of metals doped B20 vs. conventional diesel on a DPF was quantified in a laboratory controlled accelerated ash loading study. The ash loading was conducted on two DPFs – one using ULSD fuel and the other on B20 containing metals dopants equivalent to 4 ppm B100 total metals. Engine oil consumption and B20 metals levels were accelerated by a factor of 5, with DPFs loaded to 30 g/L of ash. Details of the ash loading experiment and on-engine DPF performance evaluations are presented in the companion paper (Part I). The DPFs were cleaned, and ash samples were taken from the cleaned material. X-ray Fluorescence (XRF), X-Ray Photoelectron Spectroscopy (XPS) and X-Ray Diffraction (XRD) were conducted on the ash samples.

The project objective was to generate experimental data to evaluate the impact of metals doped B20 on DPF ash loading and performance compared to that of conventional petrodiesel. Accelerated ash loading was conducted on two DPFs – one exposed to regular diesel fuel and the other to B20 containing metal dopants equivalent to 4 ppm B100 total metals (currently total metals are limited to 10 ppm in ASTM D6751, the standard for B100). Periodic performance evaluations were conducted on the DPFs at 10 g/L ash loading intervals. After the evaluations at 30 g/L, the DPF was cleaned with a commercial DPF cleaning machine and another round of DPF evaluations were conducted. A comparison of the effect of ash loading with the two fuels and DPF cleaning is presented. The metals doped B20 fuel resulted in ash that was similar to that deposited when exposed to ULSD (lube oil ash) and exhibited similar ash cleaning removal efficiency.

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.

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.

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.

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.

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.

Particulate matter (PM) and NOX are two major pollutants generated by diesel engines. Modern diesel aftertreatment systems include selective catalytic reduction (SCR) technology that helps reduce tailpipe NOX emissions when coupled with diesel exhaust fluid (DEF/urea) injection. However, this process also results in the formation of urea derived byproducts that can influence non-volatile particle number (PN) measurement conducted in accordance with the European Union (EU) Particle Measurement Program (PMP) protocol. In this program, an experimental investigation of the impact of DEF injection on tailpipe PN and its implications for PMP compliant measurements was conducted using a 2015 model year 6.7 L diesel engine equipped with a diesel oxidation catalyst, diesel particulate filter and SCR system. Open access to the engine controller was available to manually override select parameters.

Euro VI regulations in Europe and its adaptors recently extended the regulation to include Particle Number (PN) for in-use conformity testing. However, the in-use PN Portable Emissions Measurement System (PEMS) is still evolving and has higher measurement uncertainty when compared against laboratory-grade PN systems. The PN systems for laboratory require a condensation particle counter (CPC). Thus, in this study, a CPC-based Horiba PN-PEMS was selected for performance evaluation against the laboratory-grade PN systems. This study was divided into four phases. The first two phases’ measurements were conducted from the Constant Volume Sampler (CVS) tunnel where the brake-specific particle number (BSPN) levels of 1010-12 and 1013 (#/bhp-h) were measured from the engines equipped with diesel particulate filter (DPF) and without DPF, respectively. In comparison against PN systems, PN-PEMS, on average, reported 14% lower BSPN from 82 various tests for the BSPN levels of 1010-11.

As agencies and governing bodies evaluate the feasibility of reduced emission standards, additional focus has been placed on technology durability. This is seen in proposed updates, which would require Original Equipment Manufacturers (OEMs) to certify engine families utilizing a full useful life (FUL) aftertreatment system. These kinds of proposed rulings would place a heavy burden on the manufacturer to generate FUL components utilizing traditional engine aging methods. Complications in this process will also increase the product development effort and will likely limit the amount of aftertreatment durability testing. There is also uncertainty regarding the aging approach and the representative impact compared to field aged units. Existing methodologies have evolved to account for several deterioration mechanisms that, when controlled, can be utilized to create a flexible aging protocol. As a result, these methodologies provide the necessary foundation for continued development.