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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.

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.

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.

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.

With the increasing level of electrification of on-road, off-road and stationary applications, use of larger lithium-ion battery packs has become essential. These packs require large capital investments on the order of millions of dollars and pose a significant risk of self-annihilation without rigorous safety evaluation and management. Testing these larger battery packs to validate design changes can be cost prohibitive. A reliable numerical simulation tool to predict battery thermal runaway under various abuse scenarios is essential to engineer safety into the battery pack design stage. A comprehensive testing & simulation workflow has been established to calibrate and validate the numerical modeling approach with the test data for each of the individual sub model - electrochemical, internal short circuit and thermal abuse model. A four-equation thermal abuse model was built and validated for lithium-ion 21700 form factor cylindrical cells using NCA cathodes.

Onboard sensing and external connectivity using Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I) and Vehicle-to-Everything (V2X) technologies allows a vehicle to "know" its future operating environment with some degree of certainty, greatly narrowing prior information gaps. The increased development of such connected and automated vehicle systems, currently used mostly for safety and driver convenience, presents new opportunities to improve the energy efficiency of individual vehicles [1, 2, 3, 4, 5]. Southwest Research Institute (SwRI) in collaboration with Toyota Motor North America and University of Michigan is currently working on improving energy consumption of a Toyota Prius Prime 2017 by 20%. This paper will provide an overview of the various algorithms that are being developed to achieve the energy consumption target. Custom tools such as a traffic simulator was built to model traffic flow in Fort Worth, Texas with sufficient accuracy.

A new generation of vehicle dynamics and powertrain control technologies are being developed to leverage information streams enabled via vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) connectivity [1, 2, 3, 4, 5]. While algorithms that use these connected information streams to enable improvements in energy efficiency are being studied in detail, methodologies to quantify and analyze these improvements on a vehicle have not yet been explored fully. A procedure to test and accurately measure energy-consumption benefits of a connected and automated vehicle (CAV) is presented. The first part of the test methodology enables testing in a controlled environment. A traffic simulator is built to model traffic flow in Fort Worth, Texas with sufficient accuracy. The benefits of a traffic simulator are two-fold: (1) generation of repeatable traffic scenarios and (2) evaluation of the robustness of control algorithms by introducing disturbances.

Numerous studies have characterized the impact of high injection pressure and small nozzle holes on spray quality and the subsequent impact on combustion. Higher injection pressure or smaller nozzle diameter usually reduce soot emissions owing to better atomization quality and fuel-air mixing enhancement. The influence of nozzle geometry on spray and combustion of diesel continues to be a topic of great research interest. An alternate approach impacting spray quality is investigated in this paper, specifically the impact of non-circular nozzles. The concept was explored experimentally in an optically accessible constant-volume combustion chamber (CVCC). Non-reacting spray evaluations were conducted at various ambient densities (14.8, 22.8, 30 kg/m3) under inert gas of Nitrogen (N2) while injection pressure was kept at 100 MPa. Shadowgraph imaging was used to obtain macroscopic spray characteristics such as spray structure, spray penetration, and the spray cone angle.

Road tests of class 8 tractor trailers were conducted by the US Environmental Protection Agency (EPA) on a new and retreaded tires of varying rolling resistance in order to provide estimates of the quantitative relation between rolling resistance and fuel consumption. Reductions in fuel consumption were measured using the SAE J1231 (reaffirmation of 1986) test method. Vehicle rolling resistance was calculated as a load-weighted average of the rolling resistance (as measured by ISO28580) of the tires in each axle position. Both new and retreaded tires were tested in different combinations to obtain a range of vehicle coefficient of rolling resistance from a baseline of 7.7 kg/ton to 5.3 kg/ton. Reductions in fuel consumption displayed a strong linear relationship with coefficient of rolling resistance, with a maximum reduction of fuel consumption of 10 percent relative to the baseline.

A Selective Catalytic Reduction (SCR) system is a simple solution to mitigate high concentration of nitrogen oxides from tail pipe emissions using ammonia as catalyst. In recent years, implementation of stringent emission standards for diesel exhaust made the SCR system even more lucrative aftertreatment solution for diesel engine manufacturer due to its well established reaction mechanism and lower initial cost involved compared to other available options. Nitrogen oxides reduction efficiency and ammonia slip are two main parameters that affects SCR system performance. Therefore, primary design objective of an efficient SCR system is to enhance reduction of nitrogen oxides and control ammonia slip. Both these factors can be improved by having a uniform mixture of ammonia at the SCR inlet. In this mathematical simulation, various parameters that affect accuracy in predicting the uniformity of mixture at the SCR inlet have been documented.

A simulation framework with a validated system model capable of estimating fuel consumption is a valuable tool in analysis and design of the hybrid vehicles. In particular, the framework can be used for (1) benchmarking the fuel economy achievable from alternate hybrid powertrain technologies, (2) investigating sensitivity of fuel savings with respect to design parameters (for example, component sizing), and (3) evaluating the performance of various supervisory control algorithms for energy management. This paper describes such a simulation framework that can be used to predict fuel economy of series hydraulic hybrid vehicle for any specified driver demand schedule (drive cycle), developed in MATLAB/Simulink. The key components of the series hydraulic hybrid vehicle are modeled using a combination of first principles and empirical data. A simplified driver model is included to follow the specified drive cycle.

Southwest Research Institute developed an Autonomous Ground Vehicle (AGV) capable of navigating in urban environments. The paper first gives an overview of hardware and software onboard the vehicle. The systems onboard are classified into perception, intelligence, and command and control modules to mimic a human driver. Perception deals with sensing from the world and translating it into situation awareness. This awareness is then fed into intelligence modules. Intelligence modules take inputs from the user to understand the need to navigate from its current location to another destination and, then, generate a path between them on urban, drivable surfaces using its internal urban database. Situational awareness helps intelligence to update the path in real time by avoiding any static/moving obstacles while following traffic rules.

Brake energy recovery is one of the key components in today's hybrid vehicles that allows for increased fuel economy. Typically, major engineering changes are required in the drivetrain to achieve these gains. The objective of this paper is to present a concept of capturing brake energy in a mild hybrid approach without any major modifications to the drivetrain or other vehicular systems. With fuel costs rising, the additional component cost incurred in the presented concept may be recovered quickly. In today's vehicles, alternators supply the electrical power for the engine and vehicle accessories whenever the engine is running. As vehicle electrical demands increase, this load is an ever-increasing part of the engine's output, negatively impacting fuel economy. By using a regenerative device (alternator) on the drive shaft (or any other part of the power train), electrical energy can be captured during braking.

This paper analyzes the aging of zeolite based hydrocarbon traps to guide development of diagnostic algorithms. Previous research has shown the water adsorption ability of zeolite ages along with the hydrocarbon adsorption ability, and this leads to a possible diagnostic algorithm: the water concentration in the exhaust can be measured and related to aging. In the present research, engine experiments demonstrate that temperature measurements are also related to aging. To examine the relationship between temperature-based and moisture-based diagnostic algorithms, a transient, nonlinear heat and mass transfer model of the exhaust during cold-start is developed. Despite some idealizations, the model replicates the qualitative behavior of the exhaust system. A series of parametric studies reveals the sensitivity of the system response to aging and various noise factors.

In off-highway applications the engine torque is distributed between the transmission (propulsion) and other accessories such as power steering, air conditioning and implements. Electronic controls offer the opportunity to more efficiently manage the control of the engine and transmission as an integrated system. This paper deals with development of a steepest descent algorithm for maximizing the efficiency of hydrostatic transmission along with the engine in the presence of accessory load. The methodology is illustrated with an example. The strategy can be extended to the full hydro-mechanical configuration as required. Applications of this approach include adjusting for component wear and intelligent energy management between different accessories for possible size reduction of powertrain components. The potential benefits of this strategy are improved fuel efficiency and operator productivity.

This paper traces the evolution of the ASTM Test Monitoring Center (TMC) from its modest beginnings in 1976 to the present. Formed as an unbiased and non-aligned group within ASTM Subcommittee D02.B, the TMC operates a reference oil based calibration system that serves both the producers and users of automotive lubricants. Governed by the ASTM Test Monitoring Board, the center's primary mission is to calibrate engine dynamometer test stands used to conduct various ASTM test methods for evaluating lubricant performance. The core services of the TMC have remained the same over its nearly 25 year history. The center stores and distributes ASTM reference oils and is responsible for assuring, through the use of analytical testing, the quality and consistency of the oils. The number of reference oils handled by the TMC has steadily increased over time such that today the center inventories some 100 different formulations having a total volume of 65,000 gallons.

For many years the SAE No. 2 friction machine has been used to measure the coefficient of friction obtained through the interaction of fluid, steel and clutch material. In addition, by forcing energy through the wetted clutch-steel interface and measuring the decay of the coefficient of friction over time, the durability of the materials and fluids can be determined. This paper discusses the use of a numerical computer model to duplicate SAE No. 2 data. The inputs for this model include test stand geometry and physical properties as well as output from a low velocity friction apparatus (LVFA). The LVFA uses a small disc of friction material, a small disc of steel material, and a small sample of fluid to generate a coefficient versus speed curve (m vs v). It was found that torque traces and speed traces generated by this model correlate well with actual SAE No. 2 data. THERE ARE SEVERAL REASONS for creating this model.

An Emergency Tire Inflation System (ETIS) designed for use on commercial trucks was evaluated and tested. The ETIS is provided in kit form and designed to be installed by a truck operator to provide emergency air to inflate a low or punctured tire on tractor drive axles. The ETIS will continue to supply air to the tire until the system pressure falls below a safe air pressure level. The system is designed to allow the rig to be driven 500 miles to a tire repair station or to a safe location where tire repair service is available. The installation kit (Figure 1), which can fit under a truck seat, includes all the necessary equipment to install the system on the most common drive axles. The ETIS supplies air to the under-inflated tire through a previously qualified1 Rotary Union design. The Rotary Union is attached to the axle flange of the drive axle by a threaded adapter and two adjustable links that allow the Rotary Union to be placed at the center of rotation of the axle.

This paper discusses the implications of computerizing the SAE #2 clutch friction durability tests that General Motors Corporation and Ford Motor Company require for automatic transmission fluid certification. There are three reasons for this paper. 1) Friction durability testing is a significant part of a much larger battery of tests needed to qualify a fluid. 2)There have been recent modifications concerning computerization of both the Ford and GM tests. 3) Because there are only two OEM qualified testing facilities, the details of certain testing intricacies in the areas of data acquisition, reduction and reporting may not be as understood as well as in other areas of automotive-based standardized testing. Formulators of automatic transmission fluid need to be aware of all details surrounding the collection and evaluation of the data that will result in the final test report.

A theoretical model for predicting cetane number of primary reference fuels from parameters measurable by proton nuclear magnetic resonance is presented. This modeling technique is expanded to include secondary reference fuels, pure hydrocarbons, and commercial-type fuels. An evaluation of the ignition process indicated that not only hydrogen type distribution measurable by proton NMR, but also relative hydrogen population is important in predicting cetane number. Two mathematical models are developed. One predicts cetane number of saturate fuels and the second predicts cetane number of fuels containing aromatic components. The aromatic fuel model is tested using the ASTM Diesel Check Fuels and shown to predict within the standard error of the model.