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Technical Paper

V2X Communication Protocols to Enable EV Battery Capacity Measurement: A Review

2024-04-09
2024-01-2168
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).
Technical Paper

Approaches for Developing and Evaluating Emerging Partial Driving Automation System HMIs

2024-04-09
2024-01-2055
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.
Technical Paper

Extended Deep Learning Model to Predict the Electric Vehicle Motor Operating Point

2024-04-09
2024-01-2551
The transition from combustion engines to electric propulsion is accelerating in every coordinate of the globe. The engineers had strived hard to augment the engine performance for more than eight decades, and a similar challenge had emerged again for electric vehicles. To analyze the performance of the engine, the vector engine operating point (EOP) is defined, which is common industry practice, and the performance vector electric vehicle motor operating point (EVMOP) is not explored in the existing literature. In an analogous sense, electric vehicles are embedded with three primary components, e.g., Battery, Inverter, Motor, and in this article, the EVMOP is defined using the parameters [motor torque, motor speed, motor current]. As a second aspect of this research, deep learning models are developed to predict the EVMOP by mapping the parameters representing the dynamic state of the system in real-time.
Technical Paper

Performance of Spark Current Boost System on a Production Engine under Lean-Burn Conditions

2024-04-09
2024-01-2106
In order to improve the fuel economy for future high-efficiency spark ignition engines, the applications of advanced combustion strategies are considered to be beneficial with an overall lean and/or exhaust gas recirculation diluted cylinder charge. Stronger and more reliable ignition sources become more favorable under extreme lean/EGR conditions. Existing research indicates that the frequency of plasma restrikes increases with increased flow velocity and decreased discharge current level, and a higher discharge current can reduce the gap resistance and maintain the stretched plasma for a longer duration under flow conditions. An in-house developed current boost control system provides flexible control of the discharge current level and discharge duration. The current boost ignition system is based on a multi-coil system with a discharge current level of 180mA.
Technical Paper

Comprehensive Evaluation of Behavioral Competence of an Automated Vehicle Using the Driving Assessment (DA) Methodology

2024-04-09
2024-01-2642
With the development of vehicles equipped with automated driving systems, the need for systematic evaluation of AV performance has grown increasingly imperative. According to ISO 34502, one of the safety test objectives is to learn the minimum performance levels required for diverse scenarios. To address this need, this paper combines two essential methodologies - scenario-based testing procedures and scoring systems - to systematically evaluate the behavioral competence of AVs. In this study, we conduct comprehensive testing across diverse scenarios within a simulator environment following Mcity AV Driver Licensing Test procedure. These scenarios span several common real-world driving situations, including BV Cut-in, BV Lane Departure into VUT Path from Opposite Direction, BV Left Turn Across VUT Path, and BV Right Turn into VUT Path scenarios.
Research Report

Implications of Off-road Automation for On-road Automated Driving Systems

2023-12-12
EPR2023029
Automated vehicles, in the form we see today, started off-road. Ideas, technologies, and engineers came from agriculture, aerospace, and other off-road domains. While there are cases when only on-road experience will provide the necessary learning to advance automated driving systems, there is much relevant activity in off-road domains that receives less attention. Implications of Off-road Automation for On-road Automated Driving Systems argues that one way to accelerate on-road ADS development is to look at similar experiences off-road. There are plenty of people who see this connection, but there is no formalized system for exchanging knowledge. Click here to access the full SAE EDGETM Research Report portfolio.
Technical Paper

Investigation of Fuel Injection Pressure Impact on Dimethyl Ether Combustion

2023-10-31
2023-01-1644
Compression ignition engines used in heavy-duty applications are typically powered by diesel fuel. The high energy density and feedstock abundance provide a continuing source for the immense energy demand. However, the heavy-duty transportation sector is challenged with lowering greenhouse gas and combustion by-product emissions, including carbon dioxide, nitrogen oxides, and particulate matter. The continuing development of engine management and combustion strategies has proven the ability to meet current regulations, particularly with higher fuel injection pressure. Nonetheless, a transition from diesel to a renewable alternative fuel source will play a significant role in reducing greenhouse gases while maintaining the convenience and energy density inherent in liquid fuels. Dimethyl ether is a versatile fuel that possesses combustion properties suitable for compression ignition engines and physical properties helpful for clean combustion.
Technical Paper

Performance and Emission Characteristics of Direct Injection DME Combustion under Low NOx Emissions

2023-04-11
2023-01-0327
Compression ignition internal combustion engines provide unmatched power density levels, making them suitable for numerous applications including heavy-duty freight trucks, marine shipping, and off-road construction vehicles. Fossil-derived diesel fuel has dominated the energy source for CI engines over the last century. To mitigate the dependency on fossil fuels and lessen anthropogenic carbon released into the atmosphere within the transportation sector, it is critical to establish a fuel source which is produced from renewable energy sources, all the while matching the high-power density demands of various applications. Dimethyl ether (DME) has been used in non-combustion applications for several decades and is an attractive fuel for CI engines because of its high reactivity, superior volatility to diesel, and low soot tendency. A range of feedstock sources can produce DME via the catalysis of syngas.
Technical Paper

An Ultra-Light Heuristic Algorithm for Autonomous Optimal Eco-Driving

2023-04-11
2023-01-0679
Connected autonomy brings with it the means of significantly increasing vehicle Energy Economy (EE) through optimal Eco-Driving control. Much research has been conducted in the area of autonomous Eco-Driving control via various methods. Generally, proposed algorithms fall into the broad categories of rules-based controls, optimal controls, and meta-heuristics. Proposed algorithms also vary in cost function type with the 2-norm of acceleration being common. In a previous study the authors classified and implemented commonly represented methods from the literature using real-world data. Results from the study showed a tradeoff between EE improvement and run-time and that the best overall performers were meta-heuristics. Results also showed that cost functions sensitive to the 1-norm of acceleration led to better performance than those which directly minimize the 2-norm.
Technical Paper

The Effect of Exhaust Emission Conditions and Coolant Temperature on the Composition of Exhaust Gas Recirculation Cooler Deposits

2023-04-11
2023-01-0438
Exhaust Gas Recirculation (EGR) coolers are widely used on diesel engines to reduce in-cylinder NOx formation. A common problem is the accumulation of a fouling layer inside the heat exchanger, mainly due to thermophoresis that leads to deposition of particulate matter (PM), and condensation of hydrocarbons (HC) from the diesel exhaust. From a recent investigation of deposits from field samples of EGR coolers, it was confirmed that the densities of their deposits were much higher than reported in previous studies. In this study, the experiments were conducted in order to verify hypotheses about deposit growth, especially densification. An experimental set up which included a custom-made shell and tube type heat exchanger with six surrogate tubes was designed to control flow rate independently, and was installed on a 1.9 L L-4 common rail turbo diesel engine.
Journal Article

A Standard Set of Courses to Assess the Quality of Driving Off-Road Combat Vehicles

2023-04-11
2023-01-0114
Making manned and remotely-controlled wheeled and tracked vehicles easier to drive, especially off-road, is of great interest to the U.S. Army. If vehicles are easier to drive (especially closed hatch) or if they are driven autonomously, then drivers could perform additional tasks (e.g., operating weapons or communication systems), leading to reduced crew sizes. Further, poorly driven vehicles are more likely to get stuck, roll over, or encounter mines or improvised explosive devices, whereby the vehicle can no longer perform its mission and crew member safety is jeopardized. HMI technology and systems to support human drivers (e.g., autonomous driving systems, in-vehicle monitors or head-mounted displays, various control devices (including game controllers), navigation and route-planning systems) need to be evaluated, which traditionally occurs in mission-specific (and incomparable) evaluations.
Journal Article

Development of a Novel High Strength Aluminum-Cerium Based Rotor Alloy for Electric Vehicle Induction Motor Applications

2023-04-11
2023-01-0878
To increase vehicle range, light weighting of electric vehicles has been extensively researched and implemented by using aluminum intensive solutions. With regards to traction motors, aluminum alloys that have a desired combination of high electrical conductivity and strength are required for high power output and efficiency. In this research, a novel Al-Ce based alloy, with minor additions of Si and Mg for strengthening, was investigated in different heat treatment tempers to maximize mechanical properties while maintaining a high electrical conductivity. This new alloy system appears to have addressed the classic conundrum of the inverse relationship of mechanical performance verses electrical conductivity for traditional aluminum alloy systems. The results suggest that the Al-Ce-Si-Mg alloy had yield strength in excess of 120 MPa and electrical conductivity of at least 50 %IACS in the T5 and T6 conditions.
Technical Paper

Neural Network Model to Predict the Thermal Operating Point of an Electric Vehicle

2023-04-11
2023-01-0134
The automotive industry widely accepted the launch of electric vehicles in the global market, resulting in the emergence of many new areas, including battery health, inverter design, and motor dynamics. Maintaining the desired thermal stress is required to achieve augmented performance along with the optimal design of these components. The HVAC system controls the coolant and refrigerant fluid pressures to maintain the temperatures of [Battery, Inverter, Motor] in a definite range. However, identifying the prominent factors affecting the thermal stress of electric vehicle components and their effect on temperature variation was not investigated in real-time. Therefore, this article defines the vector electric vehicle thermal operating point (EVTHOP) as the first step with three elements [instantaneous battery temperature, instantaneous inverter temperature, instantaneous stator temperature].
Journal Article

Estimates of In-Vehicle Task Element Times for Usability and Distraction Evaluations

2023-04-11
2023-01-0789
Engaging in visual-manual tasks such as selecting a radio station, adjusting the interior temperature, or setting an automation function can be distracting to drivers. Additionally, if setting the automation fails, driver takeover can be delayed. Traditionally, assessing the usability of driver interfaces and determining if they are unacceptably distracting (per the NHTSA driver distraction guidelines and SAE J2364) involves human subject testing, which is expensive and time-consuming. However, most vehicle engineering decisions are based on computational analyses, such as the task time predictions in SAE J2365. Unfortunately, J2365 was developed before touch screens were common in motor vehicles.
Research Report

Legal Issues Facing Automated Vehicles, Facial Recognition, and Privacy Rights

2022-07-28
EPR2022016
Facial recognition software (FRS) is a form of biometric security that detects a face, analyzes it, converts it to data, and then matches it with images in a database. This technology is currently being used in vehicles for safety and convenience features, such as detecting driver fatigue, ensuring ride share drivers are wearing a face covering, or unlocking the vehicle. Public transportation hubs can also use FRS to identify missing persons, intercept domestic terrorism, deter theft, and achieve other security initiatives. However, biometric data is sensitive and there are numerous remaining questions about how to implement and regulate FRS in a way that maximizes its safety and security potential while simultaneously ensuring individual’s right to privacy, data security, and technology-based equality.
Research Report

Automated Vehicles: A Human/Machine Co-learning Perspective

2022-04-27
EPR2022009
Automated vehicles (AVs)—and the automated driving systems (ADSs) that enable them—are increasing in prevalence but remain far from ubiquitous. Progress has occurred in spurts, followed by lulls, while the motor transportation system learns to design, deploy, and regulate AVs. Automated Vehicles: A Human/Machine Co-learning Experience focuses on how engineers, regulators, and road users are all learning about a technology that has the potential to transform society. Those engaged in the design of ADSs and AVs may find it useful to consider that the spurts and lulls and stakeholder tussles are a normal part of technology transformations; however, this report will provide suggestions for effective stakeholder engagement. Click here to access the full SAE EDGETM Research Report portfolio.
Technical Paper

An Investigation of OME3-Diesel Fuel Blend on a Multi-Cylinder Compression Ignition Engine

2022-03-29
2022-01-0439
Oxygenated, low energy-density fuels have the potential to decouple the NOx-soot emissions trade-off in compression-ignition engines. Additionally, synthetic fuels can provide a pathway to reach carbon-neutral utilization of hydrocarbon-based fuels in IC engines. Oxymethylene Dimethyl Ether (OME) is one such synthetic, low energy-density fuel, derived from sustainable sources that in combination with conventional fossil fuels with higher energy content, has the potential to reduce CO2 emissions below the US and EU VI legislative limits, while maintaining ultra-low soot emissions. The objective of this work is to investigate and compare the performance, emissions and efficiency of a modern multi-cylinder diesel engine under conventional high temperature combustion (HTC) with two different fuels; 1) OME310 - a blend of 10% OME3 by volume, with conventional Ultra-Low Sulphur Diesel (ULSD), and 2) D100 - conventional ULSD in North America.
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