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EcoCAR 3 is a university based competition with the goal of hybridizing a 2016 Chevrolet Camaro to increase fuel economy, decrease environmental impact, and maintain user acceptability. To achieve this goal, university teams across North America must design, test, and implement automotive systems. The Colorado State University (CSU) team has designed a parallel pretransmission plug in hybrid electric design. This design will add torque from the engine and motor onto a single shaft to drive the vehicle. Since both the torque generating devices are pre-transmission the torque will be multiplied by both the transmission and final drive. To handle the large amount of torque generated by the entire powertrain system the vehicle's rear half-shafts require a more robust design. Taking advantage of this, the CSU team has decided to pursue the use of composites to increase the shaft's robustness while decreasing component weight.

Prediction of vehicle velocity is important since it can realize improvements in the fuel economy/energy efficiency, drivability, and safety. Velocity prediction has been addressed in many publications. Several references considered deterministic and stochastic approaches such as Markov chain, autoregressive models, and artificial neural networks. There are numerous new sensor and signal technologies like vehicle-to-vehicle and vehicle-to-infrastructure communication that can be used to obtain inclusive datasets. Using these inclusive datasets of sensors in deep neural networks, high accuracy velocity predictions can be achieved. This research builds upon previous findings that Long Short-Term Memory (LSTM) deep neural networks provide low error velocity prediction. We developed an LSTM deep neural network that uses different groups of datasets collected in Fort Collins, Colorado.

The environmental implications of converting vehicles powered by Internal Combustion Engines (ICE) to battery powered and hybrid battery/ICE powered are evaluated for the case of Chile, one of the worldwide leaders in the production of lithium (Li) required for manufacturing of Li-ion batteries. The economic and environmental metrics were evaluated by techno-economic analysis (TEA) and Life Cycle Assessment (LCA) tools - SuperPro Designer and Gabi®/GREET® models. The system boundary includes both the renewable and nonrenewable energy sources available in Chile and well-to-pump energy consumptions and GHG emissions due to Li mining and Li-ion battery manufacturing. All the major input data required for TEA and LCA were generated using Autonomie vehicle modeling software. This study compares economic and environmental indicators of three vehicle models for the case of Chile including compact, mid-size, and a light duty truck.

A range of cycle characteristics have been used to estimate the hybrid potential for vehicle duty cycles including characteristic acceleration, aerodynamic velocity, kinetic intensity, stop time, etc. These parameters give an indication of overall hybrid potential benefits, but do not contain information on the distribution of the available braking energy and the hybrid system power required to capture the braking energy. In this paper, the authors propose two new cycle characteristics to help evaluate overall hybrid potential of vehicle cycles: P50 and P90, which are non-dimensional power limits at 50% and 90% of available braking energy. These characteristics are independent of vehicle type, and help illustrate the potential hybridization benefit of different drive cycles. First, the distribution of available braking energy as a function of brake power for different vehicle cycles and vehicle classes is analyzed.

Maintaining and diagnosing vehicle systems often involves a technician connecting a service computer to the vehicle diagnostic port through a vehicle diagnostics adapter (VDA). This creates a connection from the service software to the vehicle network through a protocol adapter. Often, the protocols for the personal computer (PC) hosted diagnostic programs use USB, and the diagnostic port provides access to the controller area network (CAN). However, the PC can also communicate to the VDA via WiFi or Bluetooth. There may be scenarios where these wireless interfaces are not appropriate, such as maintaining military vehicles. As such, a method to defeature the wireless capabilities of a typical vehicle diagnostic adapter is demonstrated without access to the source code or modifying the hardware. The process of understanding the vehicle diagnostic adapter system, its hardware components, the firmware for the main processor and subsystems, and the update mechanism is explored.

Studies have shown that obtaining and utilizing information about the future state of vehicles can improve vehicle fuel economy (FE). However, there has been a lack of research into whether near-term technologies can be utilized to improve FE and the impact of real-world prediction error on potential FE improvements. In this study, a speed prediction method utilizing simulated vehicle-to-vehicle (V2V) communication with real-world driving data and a drive cycle database was developed to understand if incorporating near-term technologies could be utilized in a predictive energy management strategy to improve vehicle FE. This speed prediction method informs a predictive powertrain controller to determine the optimal engine operation for various prediction durations. The optimal engine operation is input into a validated high-fidelity fuel economy model of a Toyota Prius.

Autonomous truck and trailer configurations face challenges when operating in reverse due to the lack of sensing on the trailer. It is anticipated that sensor packages will be installed on existing trailers to extend autonomous operations while operating in reverse in uncontrolled environments, like a customer's loading dock. Power Line Communication (PLC) between the trailer and the tractor cannot support high bandwidth and low latency communication. This paper explores the impact of using Ethernet or a wireless medium for commercial trailer-tractor communication on the lifecycle and operation of trailer electronic control units (ECUs) from a Systems Engineering perspective to address system requirements, integration, and security. Additionally, content-based and host-based networking approaches for in-vehicle communication, such as Named Data Networking (NDN) and IP-based networking are compared.

Commercial Heavy vehicles (CHVs) are an efficient and reliable link between marine, railroad, and air transportation nodes. The vehicle braking power imposes an important constraint in the allowable vehicle speed. The compression brake augments the vehicle retarding power and is currently typically used as an on-off device by experienced drivers. Hardware and software advances allow modulation of the compression brake power through variable valve timing, and thus, enable integration of the compression brake with service brakes. To analyze how much the compression brake affects vehicle speed during braking, we develop a crank angle engine model that describes the intrinsic transient interactions between individual cylinder intake and exhaust gas process, turbocharger dynamics, and vehicle dynamics during combustion and variable brake valve timing. The model is validated using experimental data.

Cyber assurance of heavy trucks is a major concern with new designs as well as with supporting legacy systems. Many cyber security experts and analysts are used to working with traditional information technology (IT) networks and are familiar with a set of technologies that may not be directly useful in the commercial vehicle sector. To help connect security researchers to heavy trucks, a remotely accessible testbed has been prototyped for experimentation with security methodologies and techniques to evaluate and improve on existing technologies, as well as developing domain-specific technologies. The testbed relies on embedded Linux-based node controllers that can simulate the sensor inputs to various heavy vehicle electronic control units (ECUs). The node controller also monitors and affects the flow of network information between the ECUs and the vehicle communications backbone.

Modern vehicles have incorporated numerous safety-focused Advanced Driver Assistance Systems (ADAS) in the last decade including smart cruise control and object avoidance. In this paper, we aim to go beyond using ADAS for safety and propose to use ADAS technology to enable predictive optimal energy management and improve vehicle fuel economy. We combine ADAS sensor data with a previously developed prediction model, dynamic programming optimal energy management control, and a validated model of a 2010 Toyota Prius to explore fuel economy. First, a unique ADAS detection scope is defined based on optimal vehicle control prediction aspects demonstrated to be relevant from the literature. Next, during real-world city and highway drive cycles in Denver, Colorado, a camera is used to record video footage of the vehicle environment and define ADAS detection ground truth. Then, various ADAS algorithms are combined, modified, and compared to the ground truth results.

Light duty vehicle emission standards are getting more stringent than ever before as stipulated by US EPA Tier 2 Standards and LEV III regulations proposed by CARB. The research in this paper sponsored by US DoE is focused towards developing a Tier 2 Bin 2 Emissions compliant light duty pickup truck with class leading fuel economy targets of 22.4 mpg “City” / 34.3 mpg “Highway”. Many advanced technologies comprising both engine and after-treatment systems are essential towards accomplishing this goal. The objective of this paper would be to discuss key engine technology enablers that will help in achieving the target emission levels and fuel economy. Several enabling technologies comprising air-handling, fuel system and base engine design requirements will be discussed in this paper highlighting both experimental and analytical evaluations.

Current production heavy duty diesel engines have a brake thermal efficiency (BTE) between 43-46% [1]. In partnership with the United States Department of Energy (DOE) as part of the Supertruck 2 program, Cummins has undertaken a research program to develop a new heavy-duty diesel engine designed to deliver greater than 50% BTE without the use of waste heat recovery. A system level optimization focused on: increased compression ratio, higher injection rate, carefully matched highly efficient turbocharging, variable lube oil pump, variable cooling components, and low restriction after treatment designed to deliver 50% BTE at a target development point. This work will also illustrate the system level planning and understanding of interactions required to allow that same 50% BTE heavy duty diesel engine to be integrated with a waste heat recovery (WHR) system to deliver system level efficiency of 55% BTE at a single point.

The influence of big-end bore fretting on connecting rod fatigue fracture is investigated. A finite element model, including rod-bearing contact interaction, is developed to simulate a fatigue test rig where the connecting rod is subjected to an alternating uniaxial load. Comparison of the model results with a rod fracture from the fatigue rig shows good correlation between the fracture location and the peak ‘Ruiz’ criterion, rather than the peak tensile stress location, indicating the potential of fretting to initiate a fatigue fracture and the usefulness of the ‘Ruiz’ criterion as a measure of location and severity. The model is extended to simulate a full engine cycle using pressure loads from a bearing EHL analysis. A fretting map and a ‘Ruiz’ criterion map are developed for the full engine cycle, giving an indication of a safe ‘Ruiz’ level from an existing engine which has been in service for more than 5 years.

Progression of the successful engine program exemplified by the Mack ENDT675 Maxidyne Six, having an essentially constant horsepower characteristic in the operating speed range, has led to the development and production of the new Mack ENDT865, Maxidyne V-8 having similarly ordered performance at higher output. Significant advances in design to maintain reliability at high loadings including a new injection pump, a simplified oil system, and a single turbocharger arrangement are discussed, as well as a new integral engine brake. The Mack Dynatard Engine Brake is specifically covered in the second part of this paper.

Optimal energy management of hybrid electric vehicles has previously been shown to increase fuel economy (FE) by approximately 20% thus reducing dependence on foreign oil, reducing greenhouse gas (GHG) emissions, and reducing Carbon Monoxide (CO) and Mono Nitrogen Oxide (NOx) emissions. This demonstrated FE increase is a critical technology to be implemented in the real world as Hybrid Electric Vehicles (HEVs) rise in production and consumer popularity. This review identifies two research gaps preventing optimal energy management of hybrid electric vehicles from being implemented in the real world: sensor and signal technology and prediction scope and error impacts. Sensor and signal technology is required for the vehicle to understand and respond to its environment; information such as chosen route, speed limit, stop light locations, traffic, and weather needs to be communicated to the vehicle.

Research on alternative fuels has made significant progress as demands for cleaner and more efficient engine operation intensifies. Liquefied petroleum gas (LPG) can offer a potential alternative fuel route in the Diesel fuel dominated heavy-duty transportation sector due to its low cost, high anti-knock limit relative to gasoline, and reduced emission levels. In this work, experimental investigations are performed to study the effects of LPG compositions on performance, emissions, and combustion behavior of a spark-ignited (SI) cooperative fuel research (CFR) engine under stoichiometric conditions. Four LPG blends (chemically pure propane, a representative US blend, HD-5, and a representative European blend) representing the present LPG market are chosen. The impact of fuel composition is studied under different compression ratios (CR), ranging from 7:1 to 10:1 with one-unit increments, and at constant engine speed, intake manifold air pressure (IMAP) and 50% burn crank angle (CA50).

A technology path has been identified for development of a high efficiency, durable, gasoline engine, targeted at achieving performance and emissions levels necessary to meet heavy-duty, on-road standards of the foreseeable future. Initial experimental and numerical results for the proposed technology concept are presented. This work summarizes internal research efforts conducted at Southwest Research Institute. An alternative combustion system has been numerically and experimentally examined. The engine utilizes gasoline as the fuel, with a combination of enabling technologies to provide high efficiency operation at ultra-low emissions levels. The concept is based upon very highly-dilute combustion of gasoline at high compression ratio and boost levels. Results from the experimental program have demonstrated engine-out NOx emissions of 0.06 g/hp/hr, at single-cylinder brake thermal efficiencies (BTE) above thirty-four percent.

To establish a criteria for engine oil requirements for Mack diesel engines, a program was conducted to establish a specification based on the use of a production multicylinder engine. Laboratory engine tests were supplemented by field tests to assure correlation. Subsequently modifications were made to the engine test procedures to accommodate modifications in engines being marketed. Oil monitoring and oil analysis programs were also implemented to further assist in assuring adequate engine lubrication.

The performance characteristics of a commercial lean-NOX trap catalyst were evaluated between 200 and 500°C, using H2, CO, and a mixture of both H2 and CO as reductants before and after different high-temperature aging steps, from 600 to 750°C. Tests included NOX reduction efficiency during cycling, NOX storage capacity (NSC), oxygen storage capacity (OSC), and water-gas-shift (WGS) and NO oxidation reaction extents. The WGS reaction extent at 200 and 300°C was negatively affected by thermal degradation, but at 400 and 500°C no significant change was observed. Changes in the extent of NO oxidation did not show a consistent trend as a function of thermal degradation. The total NSC was tested at 200, 350 and 500°C. Little change was observed at 500°C with thermal degradation but a steady decrease was observed at 350°C as the thermal degradation temperature was increased.

Recent developments in materials science related to nano-technology have led to the creation and investigation of a new group of potential coolants known as nanofluids. These suspensions have been shown to have improved heat transfer capabilities over fluids without nanoparticles. The application of such fluids in motor racing shows potential for improvements in engine thermal management and aerodynamics. This study investigates the effect of additions of nanoparticles on the heat capacity of water using Differential Scanning Calorimetry (DSC). Fluids incorporating a variety of nanoparticles, of varying size and volume fraction, are investigated. It is shown that the volumetric heat capacity of water is only slightly affected by the addition of nanoparticles. The similarity in volumetric heat capacities, coupled with proven increased thermal conductivity of nanofluids, yields fluids with high thermal diffusivities that respond more quickly to changes in thermal environment.