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In response to global climate change, there is a widespread push to reduce carbon emissions in the transportation sector. For the difficult to decarbonize heavy-duty (HD) vehicle sector, lower carbon intensity fuels can offer a low-cost, near-term solution for CO2 reduction. The use of natural gas can provide such an alternative for HD vehicles while the increasing availability of renewable natural gas affords the opportunity for much deeper reductions in net-CO2 emissions. With this in consideration, the US National Renewable Energy Laboratory launched the Natural Gas Vehicle Research and Development Project to stimulate advancements in technology and availability of natural gas vehicles. As part of this program, Southwest Research Institute developed a hybrid-electric medium-HD vehicle (class 6) to demonstrate a substantial CO2 reduction over the baseline diesel vehicle and ultra-low NOx emissions.

The paper presents a robust adaptive control technique for precise regulation of a port fuel injection + direct injection (PFI+DI) system, a dual fuel injection configuration adopted in modern gasoline engines to boost performance, fuel efficiency, and emission reduction. Addressing parametric uncertainties on the actuators, inherent in complex fuel injection systems, the proposed approach utilizes an indirect model reference adaptive control scheme. To accommodate the increased control complexity in PFI+DI and the presence of additional uncertainties, a nonlinear plant model is employed, incorporating dynamics of the exhaust burned gas fraction. The primary objective is to optimize engine performance while minimizing fuel consumption and emissions in the presence of uncertainties. Stability and tracking performance of the adaptive controller are evaluated to ensure safe and reliable system operation under various conditions.

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.

In electric vehicle applications, the majority of the traction motors can be categorized as Permanent Magnet (PM) motors due to their outstanding performance. As indicated in the name, there are strong permanent magnets used inside the rotor of the motor, which interacts with the stator and causes strong magnetic pulling force during the assembly process. How to estimate this magnetic pulling force can be critical for manufacturing safety and efficiency. In this paper, a full 3D magnetostatic model has been proposed to calculate the baseline force using a dummy non-slotted cylinder stator and a simplified rotor for less meshing elements. Then, the full 360 deg model is simplified to a half-pole model based on motor symmetry to save the simulation time from 2 days to 2 hours. A rotor position sweep was conducted to find the maximum pulling force position. The result shows that the max pulling force happens when the rotor is 1% overlapping with the stator core.

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.

Level 2 (L2) partial driving automation systems are rapidly emerging in the marketplace. L2 systems provide sustained automatic longitudinal and lateral vehicle motion control, reducing the need for drivers to continuously brake, accelerate and steer. Drivers, however, remain critically responsible for safely detecting and responding to objects and events. This paper summarizes variations of L2 systems (hands-on and/or hands-free) and considers human drivers’ roles when using L2 systems and for designing Human-Machine Interfaces (HMIs), including Driver Monitoring Systems (DMSs). In addition, approaches for examining potential unintended consequences of L2 usage and evaluating L2 HMIs, including field safety effect examination, are reviewed. The aim of this paper is to guide L2 system HMI development and L2 system evaluations, especially in the field, to support safe L2 deployment, promote L2 system improvements, and ensure well-informed L2 policy decision-making.

A linear parameter-varying model predictive control (LPVMPC) is proposed to enhance the longitudinal vehicle speed control of a gas-engine vehicle, with potential application in autonomous vehicles. To achieve this objective, an advanced vehicle dynamic model and a sophisticated fuel consumption model are derived, forming a control-oriented model for the proposed control system. The vehicle dynamic model accurately captures the motions of the tires and the vehicle body. The fuel consumption model incorporates new powertrain modes such as automatic engine stop/start, active fuel management, and deceleration fuel cut-off, etc. The performance of the proposed LPV-MPC is evaluated by comparing it to a PID controller. Both simulation tests and vehicle-in-the-loop tests demonstrate the superior performance of the proposed controller. The results indicate that the LPV-MPC provides improved longitudinal vehicle speed control and reduced fuel consumption.

Electric vehicles (EV) present distinctive challenges compared to ICE (Internal Combustion Engine) powered counterparts. Cabin heating and air-conditioning stand out among them, especially cabin heating in cold weather, owing to its outsized effect on drivable range of the vehicle. Efficient management of the cabin thermal system has the potential to improve vehicle range without compromising passenger comfort. A method to improve cabin thermal system regulation by effectively leveraging the solar load on the vehicle is proposed in this work. The methodology utilizes connectivity and mapping data to predict the solar load over a future time horizon. Typically, the solar load is treated as an unmeasured external disturbance which is compensated with control. It can however be treated as an estimated quantity with potential to enable predictive control. The solar load prediction, coupled with a passenger thermal comfort model, enables preemptive thermal system control over a route.

DC fast charging (DCFC) also referred to as L3 charging, is the fastest charging technology to replenish the drivable range of an electric vehicle. DCFC provides the convenience of faster charging time compared to L1 and L2 at the expense of potentially increased battery health degradation. It is known to accelerate battery capacity fade leading to reduced range and lifetime of the EV battery. While there are active efforts and several means to reduce the downsides of DCFC at cell chemistry level, this trade-off is still an important consideration for most battery cells in automotive propulsion applications. Since DCFC is a customer driven technology, informing drivers of the trade-off of each DCFC event can potentially result in better outcomes for the EV battery life. Traditionally, the driver is advised to limit DCFC events without providing quantifiable metrics to inform their decisions during EV charging.

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.

Engine knock is one of the limiting factors in determining the compression ratio and engine efficiency for spark ignited engines. Using the Southwest Research Institute Knock-CoV test method, it was previously shown that the knock limited load versus combustion phasing (CA50) has a constant slope. All of the knock mitigation strategies tested provided a shift to these knock limited loads but also increased the slope. That is, for the same CA50 retard the knock limited load could be increased more. Our hypothesis was that due to fuel sensitivity, or the difference between the RON and MON, the reactions that lead to knock will behave differently as the pressure-temperature history changes with engine speeds and loads. The fuel affects on the knock and CoV limits were studied by testing fuels with various sensitivities including methanol, E85 (85% ethanol) and Iso-octane.

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.

Off-road diesel engines remain one of the most significant contributors to the overall oxides of nitrogen (NOX) inventory and the California Air Resources Board (CARB) has indicated that reductions of up to 90% from current standards may be necessary to achieve its air quality goals. In recognition of this, CARB has funded a program aimed at demonstrating emission control technologies for off-road engines. This program builds on previous efforts to demonstrate Low NOX technologies for on-road engines. The objective was to demonstrate technologies to reduce tailpipe NOX and particulate matter (PM) emissions by 90 and 75%, respectively, from the current Tier 4 Final standards. In addition, the emission reductions were to be achieved while also demonstrating a 5 to 8.6% carbon dioxide (CO2) reduction and remaining Greenhouse Gas (GHG) neutral with respect to nitrous oxide (N2O) and methane (CH4).

In the context of vehicle electrification, improving vehicle aerodynamics is not only critical for efficiency and range, but also for driving experience. In order to balance the necessary trade-offs between drag and downforce without significant impact on the vehicle styling, we see an increasing amount of active aerodynamic solutions on high-end passenger vehicles. Active rear spoilers are one of the most common active aerodynamic features. They deploy at high vehicle speed when additional downforce is required [1, 2]. For a vehicle with an active rear spoiler, the aerodynamic performance is typically predicted through simulations or physical testing at different static spoiler positions. These positions range from fully stowed to fully deployed. However, this approach does not provide any information regarding the transient effects during the deployment of the rear spoiler, which can be critical to understanding key performance aspects of the system.

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.

Electric motor whine is a major NVH source for electric vehicles. Traditional mitigation methods focus on e-motor hardware optimization, which requires long development cycles and may not be easily modified when the hardware is built. This paper presents a control- and software-based strategy to reduce the most dominant motor order of an IPM motor for General Motors’ Ultium electric propulsion system, using the patented active Torque Ripple Cancellation (TRC) technology with harmonic current injection. TRC improves motor NVH directly at the source level by targeting the torque ripple excitations, which are caused by the electromagnetic harmonic forces due to current ripples. Such field forces are actively compensated by superposition of a phase-shifted force of the same spatial order by using of appropriate current.

General Motors (GM) is working towards a future world of zero crashes, zero emissions and zero congestion. It’s “Ultium” platform has revolutionized electric vehicle drive units to provide versatile yet thrilling driving experience to the customers. Three variants of traction power inverter modules (TPIMs) including a dual channel inverter configuration are designed in collaboration with LG Magna e-Powertrain (LGM). These TPIMs are integrated with other power electronics components inside Integrated power electronics (IPE) to eliminate redundant high voltage connections and increase power density. The developed power module from LGM has used state-of-the art sintering technology and double-sided cooled structure to achieve industry leading performance and reliability. All the components are engineered with high level of integration skills to utilize across TPIM variants.

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.

Electric motor noise mitigation is a challenge in electric vehicles (EVs) due to the lack of engine masking noise. The design of the electric motor mounting configuration to the motor housing has significant impacts on the radiated noise of the drive unit. The stator can be bolted or interference-fit with the housing. A bolted stator creates motor whine and vibration excited by the motor torque ripple at certain torsional resonance frequencies. A stator with interference fit configuration stiffens the motor housing and pushes resonances to a higher frequency range, where masking noise levels are higher at faster vehicle speeds. However, this comes with additional cost and manufacturing process and may impact motor efficiency due to high stress on stators. In this paper, a thin sheet metal NVH ring is developed as a tunable stiffness device between the stator and the motor housing. It is pre-compressed and provides additional torsional rigidity to mitigate torsional excitations.