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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.

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.

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 U.S. Environmental Protection Agency (EPA) certifies gasoline deposit control additives for intake valve deposit (IVD) control utilizing ASTM D5500, a vehicle test using a1985 BMW 318i. Concerns with the age of the test fleet, its relevance in the market today, and the availability of replacement parts led the American Chemistry Council’s (ACC) Fuel Additive Task Group (FATG) to begin a program to develop a replacement. General Motors suggested using a 2.4L LE9 test engine mounted on a dynamometer and committed to support the engine until 2030. Southwest Research Institute (SwRI®) was contracted to run the development program in four Phases. In Phase I, the engine test stand was configured, and a test fuel selected. In Phase II, a series of tests were run to identify a cycle that would build an acceptable level of deposits on un-additized fuel. In Phase III, the resultant test cycle was examined for repeatability.

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.

Efficiency testing of hybrid-electric vehicles is challenging, because small run-to-run differences in pedal application can change when the engine fires or the when the friction brakes supplement regenerative braking, dramatically affecting fuel use or energy regeneration. Electronic accelerator control has existed for years, thanks to the popularity of throttle-by-wire (TBW). Electronic braking control is less mature, since most vehicles don’t use brake-by-wire (BBW). Computer braking control on a chassis dynamometer typically uses a mechanical actuator (which may suffer backlash or misalignment) or braking the dynamometer rather than the vehicle (which doesn’t yield regeneration). The growth of electrification and autonomy provides the means to implement electronic brake control. Electrified vehicles use BBW to control the split between friction and regenerative braking. Automated features, e.g. adaptive cruise control, require BBW to actuate the brakes without pedal input.

Connected and automated driving technology is known to improve real-world vehicle efficiency by considering information about the vehicle’s environment such as traffic conditions, traffic lights or road grade. This study shows how the powertrain of a hybrid-electric vehicle realizes those efficiency benefits by developing methods to directly measure real-time transient power losses of the vehicle’s powertrain components through chassis-dynamometer testing. This study is a follow-on to SAE Technical Paper 2019-01-0116, Test Methodology to Quantify and Analyze Energy Consumption of Connected and Automated Vehicles [1], to understand the sources of efficiency gains resulting from connected and automated vehicle driving. A 2017 Toyota Prius Prime was instrumented to collect power measurements throughout its powertrain and driven over a specific driving schedule on a chassis dynamometer.

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.

The process of developing, parameterizing, validating, and maintaining models occurs within a wide variety of tools, and requires significant time and resources. To maximize model utilization, models are often shared between various toolsets and experts. One common example is sharing aircraft engine models with airframers. The functionality of a given model may be utilized and shared with a secondary model, or multiple models may run collaboratively through co-simulation. There are many technical challenges associated with model sharing and co-simulation. For example, data communication between models and tools must be accurate and reliable, and the model usage must be well-documented and perspicuous for a user. This requires clear communication and understanding between computer scientists and engineers. Most often, models are developed by engineers, whereas the tools used to share the models are developed by computer scientists.

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.

To enable the evaluation of off-calibration powertrain operation, a selective interrupt and control (SIC) test capability was developed as part of an EPA evaluation of a 1.6 L EcoBoost® engine. A control and data acquisition device sits between the stock powertrain controller and the engine; the device selectively passes through or modifies control signals while also simulating feedback signals. This paper describes the development process of SIC that enabled a test engineer to command off-calibration setpoints for intake and exhaust cam phasing as well as ignition timing without the need for an open ECU duplicating the stock calibration. Results are presented demonstrating the impact of ignition timing and cam phasing on engine efficiency. When coupled with combustion analysis and crank-domain data acquisition, this test configuration provides a complete picture of powertrain performance.

Since the turn of the millennium, automated vehicle technology has matured at an exponential rate, evolving from research largely funded and motivated by military and agricultural needs to a near-production market focused on everyday driving on public roads. Research and development has been conducted by a variety of entities ranging from universities to automotive manufacturers to technology firms demonstrating capabilities in both highway and urban environments. While this technology continues to show promise, corner cases, or situations outside the average driving environment, have emerged highlighting scenarios that impede the realization of full automation anywhere, anytime. This paper will review several of these corner cases and research deficiencies that need to be addressed for automated driving systems to be broadly deployed and trusted.

The Department of Transportation (DOT) National Highway Traffic Safety Administration (NHTSA) awarded a contract to Southwest Research Institute (SwRI) to conduct research and testing in the interest of motorcoach fire safety. The goal of this program was to develop and validate procedures and metrics to evaluate current and future detection, suppression, and exterior fire-hardening technologies that prevent or delay fire penetration into the passenger compartment of a motorcoach - in order to increase passenger evacuation time. The program was initiated with a literature review and characterization of the thermal environment of motorcoach fires and survey of engine compartments, firewalls, and wheel wells of motorcoaches currently in North American service. These characterizations assisted in the development of test methods and identification of the metrics for analysis. Test fixtures were designed and fabricated to simulate a representative engine compartment and wheel well.

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.

This presentation will cover an overview of challenges and key discussion points for advanced electric motor and drive testing . Voiko will visit some examples of how D&V approaches these issues and also some suggestions for how the industry can view these intriguing problems as opportunities. The presentation will also delve into current testing developments that involve resolver, load bank and power measurement devices by highlighting solutions in the market today. There will also be a cursory look into the future of electric motor testing and what we can expect in the near term. Presenter Voiko Loukanov, D&V Electronics Limited

With the rapid expansion of the automotive market in China, air quality in the major cities has become a severe concern. Great efforts have been made in introducing new emission regulations; however, fuel and lubricant qualities, emissions aftertreatment system durability and in-use compliance to the emissions regulations still require significant improvement. China follows the European Union (EU) emission regulations in general, but different levels of standards exist. This paper gives a comprehensive overview of the current and near-future heavy-duty diesel emission regulations, as well as fuel and lubricant specifications.

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.