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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.

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.

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).

The widely accepted best practice for spark-ignition combustion is the four-valve pent-roof chamber using a central sparkplug and incorporating tumble flow during the intake event. The bulk tumble flow readily breaks up during the compression stroke to fine-scale turbulent kinetic energy desired for rapid, robust combustion. The natural gas engines used in medium- and heavy-truck applications would benefit from a similar, high-tumble pent-roof combustion chamber. However, these engines are invariably derived from their higher-volume diesel counterparts, and the production volumes are insufficient to justify the amount of modification required to incorporate a pent-roof system. The objective of this multi-dimensional computational study was to develop a combustion chamber addressing the objectives of a pent-roof chamber while maintaining the flat firedeck and vertical valve orientation of the diesel engine.

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.

Positive displacement pumps are key components in automotive and hydraulic fluid systems, often serving as the primary power source and a major source of noise in both on-highway and off-highway vehicles. Specifically, gerotor pumps are widely utilized in vehicle coolant, lubricating, and other fluid systems for both conventional and electric powertrains. This study introduces a novel method for predicting noise in gerotor pumps by combining a Computational Acoustics (CA) approach with a 3D Computational Fluid Dynamics (CFD) approach, both implemented in the Simerics–MP+ code. The CFD simulation includes the detailed transient motion of the rotors (including related mesh motion) and models the intricate cavitation/air release phenomena at varying pump speeds. The acoustic simulation employs a Ffowcs–Williams Hawkings (FW–H) integral formulation to predict sound generation and propagation based on the detailed flow field predictions from the CFD model.

This article analyzes the aerodynamic performance of Class 8 tractor-trailer geometries made available by the Environmental Protection Agency (EPA) using CFD simulation. Large Eddy Simulations (LES) were carried out with the CFD package, Simerics-MP+. A Sleeper tractor and a 53-foot box trailer configuration was considered. The configuration featured a detailed underbody, an open-grille under-hood engine compartment, mirrors, and the radiator and condenser. Multiple tractor-trailer variants were studied by adding aerodynamic surfaces to the baseline geometries. These include tank fairings and side extenders for the cabins, two types of trailer skirts, and a trailer tail. The effect of these devices towards reducing the overall vehicle drag was investigated. Mesh generation was carried out directly on the given geometry, without any surface modifications, using Simerics’ Binary-Tree unstructured mesher.

The study focuses on understanding the air and oil flow characteristics within a ball bearing during high-speed rotation, with a particular emphasis on optimizing frictional heat dissipation and oil lubrication methods. Computational fluid dynamics (CFD) techniques are employed to analyze the intricate three-dimensional airflow and oil flow patterns induced by the motion of rotating and orbiting balls within the bearing. A significant challenge in conducting three-dimensional CFD studies lies in effectively resolving the extremely thin gaps existing between the balls, races, and cages within the bearing assembly. In this research, we adopt the ball-bearing structured meshing strategy offered by Simerics-MP+ to meticulously address these micron-level clearances, while also accommodating the rolling and rotation of individual balls. Furthermore, we investigate the impact of different designs of the lubrication ports to channel oil to other locations compared to the ball bearings.

With the advent of this new era of electric-driven automobiles, the simulation and virtual digital twin modeling world is now embarking on new sets of challenges. Getting key insights into electric motor behavior has a significant impact on the net output and range of electric vehicles. In this paper, a complete 3D CFD model of an Electric Motor is developed to understand its churning losses at different operating speeds. The simulation study details how the flow field develops inside this electric motor at different operating speeds and oil temperatures. The contributions of the crown and weld endrings, crown and weld end-windings, and airgap to the net churning loss are also analyzed. The oil distribution patterns on the end-windings show the effect of the centrifugal effect in scrapping oil from the inner structures at higher speeds. Also, the effect of the sump height with higher operating speeds are also analyzed.

Modern gearboxes are meticulously engineered with three primary objectives: enhancing load-carrying capacity, minimizing noise, vibration, and harshness (NVH), and optimizing efficiency. Efficiency, in particular, holds paramount significance due to gearboxes’ substantial influence on energy consumption. One effective strategy for boosting efficiency involves curbing churning losses, stemming from the movement of oil within the gearbox housing. Computational fluid dynamics (CFD) techniques have emerged as invaluable tools for visualizing oil flow dynamics within gearboxes and pinpointing avenues for mitigating churning losses. In the context of electric vehicles (EVs), specifically battery electric vehicles (BEVs), extending their driving range is a top priority. Achieving this hinges on the design of an efficient gearbox.

Churning loss is an important energy loss term for rolling bearings at high-speed condition. However, it is quite challenging to accurately calculate the churning loss. A CFD study based on unsteady Reynolds-Averaged-Navier-Stokes that resolves the gas-liquid interface was performed to examine the unsteady multiphase flow in a roller/ball bearing. In this study, the rotating motion of the cage, races, rollers/balls about the shaft as well as self-rotation of rollers/balls about their own axis were accounted to accurately predict the oil distribution in various parts of the bearings. A novel meshing strategy is presented to resolve thin gaps between the roller/balls and the races/cage while preserving the shape of balls/rollers, races and cage. Five rotational speeds of the shaft have been examined for roller bearing and ball bearing respectively. Additionally, effect of clearance between roller/balls and races is investigated.

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.

The thermal performance of an engine coolant system is efficient when the engine head temperature is maintained within its optimum working range. For this, it is desired that air should not be entrapped in the coolant system which can lead to localized hot spots at critical locations. However, it is difficult to eliminate the trapped air pockets completely. So, the target is to minimize the entrapped air as much as possible during the coolant filling and deaeration processes, especially in major components such as the radiator, engine head, pump etc. The filling processes and duration are typically optimized in an engine test stand along with design changes for augmenting the coolant filling efficiency. However, it is expensive and time consuming to identify air entrapped locations in tests, decide on the filling strategy and make the design changes in the piping accordingly.

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.

Conventional diesel combustion (CDC) is known to provide high efficiency and reliable engine performance, but often associated with high particulate matter (PM) and nitrogen oxides (NOX) emissions. Combustion of fossil diesel fuel also produces carbon dioxide (CO2), which acts as a harmful greenhouse gas (GHG). Renewable and low-carbon fuels such as renewable diesel (RD) and methanol can play an important role in reducing harmful criteria and CO2 emissions into the atmosphere. This paper details an experimental study using a single-cylinder research engine operated under dual-fuel combustion using methanol and RD. Various engine operating strategies were used to achieve diesel-like fuel efficiency. Measurements of engine-out emissions and in-cylinder pressure were taken at test conditions including low-load and high-load operating points.

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.

Low carbon emissions policies for the transportation sector have recently driven more interest in using low net-carbon fuels, including biodiesel. An internal combustion engine (ICE) can operate effectively using biodiesel while achieving lower engine-out emissions, such as soot, mostly thanks to oxygenate content in biodiesel. This study selected a heavy-duty (HD) single-cylinder engine (SCE) platform to test biodiesel fuel blends with 20% and 100% biodiesel content by volume, referred to as B20, and B100. Test conditions include a parametric study of exhaust gas recirculating (EGR), and the start of injection (SOI) performed at low and high engine load operating points. In-cylinder pressure and engine-out emissions (NOX and soot) measurements were collected to compare diesel and biodiesel fuels.

Alternative fuels such as methanol can significantly reduce greenhouse gas (GHG) emissions when used in internal combustion engines (ICEs). This study characterized the combustion of methanol, methanol/diesel, and methanol/renewable diesel numerically. Numerical findings were also compared with engine experiments using a single-cylinder engine (SCE). The engine was operated under a dual-fuel combustion mode: methanol was fumigated at the intake port, and diesel was injected inside the cylinder. The characteristic of ignition delay trend as methanol concentration increased is being described at low temperature (low engine load) and high temperature (high engine load) conditions.