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The electrification of accessories using a fuel cell as an auxiliary power unit reduces the load on the engine and provides opportunities to increase propulsion performance or reduce engine displacement. The SunLine™ Class 8 tractor electric accessory integration project is a United States Army National Automotive Center (NAC™) initiative in partnership with Cummins Inc., Dynetek™ Industries Ltd., General Dynamics C4 Systems, Acumentrics™ Corporation, Michelin North America, Engineered Machine Products (EMP™), Peterbilt™ Motors Company, Modine™ Manufacturing and Masterflux™. Southwest Research Institute is the technical integration contractor to SunLine™ Services Group. In this paper the SunLine™ tractor electric Air Conditioning (AC) system is described and the installation of components on the tractor is illustrated. The AC system has been designed to retrofit into an existing automotive system and every effort was made to maintain OEM components whenever modifications were made.

Internal short-circuit in cells/batteries is a phenomenon where there is direct electrical contact between the positive and negative electrodes leading to thermal runaway. The nail penetration tests were used to simulate an internal short circuit within the battery, where a conductive nail was used to pierce the battery cell separator membrane which provided direct electrical contact between the positive and negative electrodes. The batteries tested during this work were common batteries used in existing automotive applications, and they included a nickel manganese cobalt (NMC) battery from a Chevrolet Bolt, a lithium manganese oxide (LMO) battery from a Chevrolet Volt, and a lithium iron phosphate (LFP) battery in a hybrid transit bus. The battery abuse and emissions tests were designed to intentionally drive the three different battery chemistries into thermal runaway while measuring battery temperatures, battery voltages and gaseous emissions.

Internal short-circuit in cells/batteries is a phenomenon where there is direct electrical contact between the positive and negative electrodes leading to thermal runaway. The nail penetration tests were used to simulate an internal short circuit within the battery, where a conductive nail was used to pierce the battery cell separator membrane which provided direct electrical contact between the positive and negative electrodes. The batteries tested during this work were common batteries used in existing automotive applications, and they included a nickel manganese cobalt (NMC) battery from a Chevrolet Bolt, a lithium manganese oxide (LMO) battery from a Chevrolet Volt, and a lithium iron phosphate (LFP) battery in a hybrid transit bus. The battery abuse and emissions tests were designed to intentionally drive the three different battery chemistries into thermal runaway while measuring battery temperatures, battery voltages and gaseous emissions.

As the efforts to push capabilities of current engine hardware to their durability limits increases, more accurate and reliable analysis is necessary to ensure that designs are robust. This paper evaluates a method of Conjugate Heat Transfer (CHT) analysis for a gasoline and a diesel engine that combines combustion Computational Fluid Dynamics (CFD), engine Finite Element Analysis (FEA), and cooling jacket CFD with the goal of obtaining more accurate temperature distribution and heat loss predictions in an engine compared to standard de-coupled CFD and FEA analysis methods. This novel CHT technique was successfully applied to a 2.5 liter GM LHU gasoline engine at 3000 rpm and a 15.0 liter Cummins ISX heavy duty diesel engine operating at 1250 rpm. Combustion CFD simulations results for the gasoline and diesel engines are validated with the experimental data for cylinder pressure and heat release rate.

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.

Until recently, U.S. government efforts to dramatically reduce emissions, greenhouse gases and vehicle fuel consumption have primarily focused on passenger car applications. Similar aggressive reductions need to be extended to heavy vehicles such as delivery trucks, buses, and motorhomes. However, the wide range of torques, speeds, and powers that such vehicles must operate under makes it difficult for any current powertrain system to provide the desired improvements in emissions and fuel economy. Hybrid electric powertrains provide the most promising, near-term technology that can satisfy these requirements. This paper highlights the configuration and benefits of a hybrid electric powertrain capable of operating in either a parallel or series mode. It describes the hybrid electric components in the system, including the electric motors, power electronics and batteries.

As on-highway, heavy-duty diesel engine designs have evolved to meet tighter emissions specifications and greater customer requirements, the crankcase environment for heavy-duty engine lubricants has changed. Engine lubricant quality is very important to help ensure engine durability, engine performance, and reduce maintenance downtime. Beginning in the late 1980's, a new Mack genuine oil specification and a new American Petroleum Institute (API) heavy-duty engine lubricant category have been introduced with each new U.S. heavy-duty, on-highway emissions specification. This paper documents the history and development of the Mack T-7, T-8, T-8A, T-8E, T-9, T-10, T-11, and T-12 engine lubricant tests.

There is an ongoing proliferation of electric and electrified vehicles as manufacturers seek to reduce their carbon footprint and meet the carbon reduction targets mandated by governments around the world. An ongoing challenge in electric vehicle design is the efficient and safe design of battery packs. There are significant safety challenges for lithium battery packs relating to thermal runaway, which can be initiated through overheating and internal short from defects or external damage. This work proposes a robust method to couple the mechanical damage in a battery module calculated from a dynamic model with a thermal model of the battery that includes heating from electro-chemical sources as well as Arrhenius reactions from the battery cells. The authors identify the main sources of thermal runaway initiation and propagation in an impact scenario simulating a vehicle collision. The modeling approach was developed and validated using test data.

Next generation vehicles are under environmental and economic pressure to reduce emissions and increase fuel economy, while maintaining the same ride and performance characteristics of present day combustion engine automobiles. This has prompted researchers to investigate hybrid vehicles as one possible solution to this challenge. At Southwest Research Institute (SwRI), a unique parallel hybrid drivetrain was designed and prototyped. This hybrid drivetrain alleviates the disadvantages of series hybrid drivetrains by directly coupling the driving wheels to two power sources, namely an engine and an electric motor. At the same time, the design allows the engine speed to be decoupled from the vehicle speed, allowing the engine to operate at its most efficient state. This paper describes the drivetrain, its components, and the test stand that was assembled to test the parallel hybrid drivetrain.

A physics-based spark ignition model was developed and integrated into a commercial CFD code. The model predicted the spark discharge process based on the electrical parameters of the secondary ignition circuit, tracked the spark motion as it was stretched by in-cylinder gas motion, and determined the resulting energy deposition to the gas. In concert with the existing kinetic solver in the CFD code, the resulting ignition and flame propagation processes were simulated. The model results have been validated against both imaging rig experiments of the spark in moving air and against engine experimental data. The model was able to replicate the key features of the spark and to capture the cyclic variability of high-dilution combustion when multiple engine cycles were simulated.

Existing expert systems have a high percentage agreement with human experts in a particular field in many situations. However, in many ways their overall behavior is not like that of a human expert. These areas include the inability to give flexible, functional explanations of their reasoning processes and the failure to degrade gracefully when dealing with problems at the periphery of their knowledge. These two important shortcomings can be improved when the right knowledge is available to the system. This paper presents an expert system design, called the Integrated Diagnostic Model (IDM), that integrates two sources of knowledge: a shallow, empirically-oriented, experiential knowledge base and a deep, functionally-oriented, physical knowledge base. To demonstrate the IDM's usefulness in the problem area of diagnosis and repair of electrical and mechanical devices, two implementations and our experience with them is described.

A unique system has been devised to measure and telemeter critical temperatures of reciprocating engine components. A prototype has been used to measure the piston pin bearing temperature in a full-scale EMD 2-567D diesel engine.

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.

An airflow-dominant control system was developed to provide precise engine and exhaust treatment control with low air fuel ratio alternative combustion. The main elements of the control logic include a real-time state observer for in-cylinder oxygen mass estimation, a simplified packaging scheme for all air-handling and fueling parameters, a finite state machine for control mode switching, combustion control models to maintain robust alternative combustion during transients, and smooth rich/lean switching during lean NOx trap (LNT) regeneration without post injection. The control logic was evaluated on a passenger car equipped with a 4-way catalyst system with LNT and was instrumental in achieving US Tier II Bin 5 emission targets with good drivability and low NVH.

Fuel costs to operate large trucks have risen substantially in the last few years and, based on petroleum supply/demand curves, that trend is expected to continue for the foreseeable future. Non-propulsion or parasitic loads in a large truck account for a significant percentage of overall engine load, leading to reductions in overall vehicle fuel economy. Electrification of parasitic loads offers a way of minimizing non-propulsion engine loads, using the full motive force of the engine for propulsion and maximizing vehicle fuel economy. This paper covers the integration and testing of electrified accessories, powered by a fuel cell auxiliary power unit (APU) in a Class 8 tractor. It is a continuation of the efforts initially published in SAE paper 2005-01-0016.

During city traffic or heavily congested roads, a vehicle can consume a substantial amount of fuel idling when the vehicle is stopped. Due to regulation enforcement, auto manufacturers are developing systems to increase the mileage and reduce emissions. Turning off the engine at traffic lights and regenerative braking systems are simple ways to reduce emissions and fuel consumption. In order to develop strong manufacturer and consumer interest, this type of operation needs to be automated such that the stop/start functionality requires no driver interaction and takes place without the intervention of the vehicle operator. Valeo Electrical Systems has developed such a system that replaces the OEM engine alternator with a starter/alternator driven by a standard multi-ribbed V belt. To avoid a break and dual voltage network, this system is based on a 12V electrical system using an Enhanced Power Supply.

Usage of CVTs in automotive applications has begun to increase, however because of their relative newness and previous usage in nonautomotive applications, a broad base of technical information on the various types of CVT's does not exist. Most importantly though, no comparison information exists on the different types of configurations. Currently, there are a number of CVT technologies that have been used in automotive, off-road and industrial applications. This paper will highlight the characteristics, design limitations and efficiencies of the following basic CVT types:

Despite considerable progress towards clean air in previous decades, parts of the United States continue to struggle with the challenge of meeting the ambient air quality targets for smog-forming ozone mandated by the U.S. EPA, with some of the most significant challenges being seen in California. These continuing issues have highlighted the need for further reductions in emissions of NOX, which is a precursor for ozone formation, from a number of key sectors including the commercial vehicle sector. In response, the California Air Resources Board (CARB) embarked on a regulatory effort culminating in the adoption of the California Heavy-Duty Low NOX Omnibus regulation.[1] This regulatory effort was supported by a series of technical programs conducted at Southwest Research Institute (SwRI).

This paper analyzes the hybridization of a conventionally powered light duty front wheel drive pick up truck by adding an electric motor driven rear axle. Also studied are the effects of using propane fuel instead of gasoline. This hybrid powertrain configuration can be described as a parallel hybrid electric vehicle. Supervisory power management control has been developed to best determine the proportion of load to be provided by the engine and/or electric motor. To perform these analyses, a simulation tool (computer model of the powertrain components) was developed using MATLAB/SIMULINK'. The models account for the thermal and mechanical efficiencies of the components and are designed to develop control strategies for meeting road loads with improved fuel economy and reduced emissions. Results of this study have shown that fuel economy can be improved and emissions reduced using commercially available components (motor, rear axle, and lead acid batteries).

1Increasing adoption of downsized, boosted, spark-ignition engines has improved vehicle fuel economy, and continued improvement is desirable to reduce carbon emissions in the near-term. However, this strategy is limited by damaging preignition events which can cause hardware failure. Research to date has shed light on various contributing factors related to fuel and lubricant properties as well as calibration strategies, but the causal factors behind an individual preignition cycle remain elusive. If actionable precursors could be identified, mitigation through active control strategies would be possible. This paper uses artificial neural networks to search for identifiable precursors in the cylinder pressure data from a large real-world data set containing many preignition cycles. It is found that while follow-up preignition cycles in clusters can be readily predicted, the initial preignition cycle is not predictable based on features of the cylinder pressure.