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The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is currently modeling and bench testing powertrain components for a parallel plug-in hybrid electric vehicle (PHEV). The custom powertrain is being implemented in a 2016 Chevrolet Camaro for the EcoCAR 3 competition. The engine, a General Motors (GM) L83 5.3L V8 with Active Fuel Management (AFM) from a 2014 Silverado, is of particular importance for vehicle integration and functionality. The engine is one of two torque producing components in the powertrain. AFM allows the engine to deactivate four of the eight cylinders which is essential to meet competition goals to reduce petroleum energy use and greenhouse gas emissions. In-vehicle testing is performed with a 2014 Silverado on a closed course to understand the criteria to activate AFM. Parameters required for AFM activation are monitored by recording vehicle CAN bus traffic.

For metallic tanks in contact with aqueous solution, it is always observed the presence of electrochemical corrosion. This process can cause both economic and environmental damage. In the automotive industry, fuel tanks systems have been studied in order to propose new materials to replace the plastic tanks or tanks with metallic coatings. Plastic tanks have the disadvantage of not being recyclable. In the other hand, for metallic coated tanks, tin is used as a coat material and, for this reason, the external tank side must be painted, making its productive process more expensive and generating higher amount of waste. Nowadays, organic-metallic coated tanks, in which, nickel and aluminum are the metals present, can be found. These coatings show potential application; because they do not use heavy metals in their composition and they do not require external painting, allowing a lower production cost.

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2008 - 2011 EcoCAR: The NeXt Challenge Advanced Vehicle Technology Competition series organized by Argonne National Laboratory (ANL) and sponsored by General Motors (GM) and the U.S. Department of Energy (DoE). Following GM's vehicle development process, HEVT established goals that meet or exceed the competition requirements for EcoCAR in the design of a plug-in, range-extended hybrid electric vehicle. The challenge involves designing a crossover SUV powertrain to reduce fuel consumption, petroleum energy use and well-to-wheels (WTW) greenhouse gas (GHG) emissions. In order to interface with and control the vehicle, the team added a National Instruments (NI) CompactRIO (cRIO) to act as a hybrid vehicle supervisory controller (HVSC).

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2009 - 2011 EcoCAR: The NeXt Challenge Advanced Vehicle Technology Competition series organized by Argonne National Lab (ANL), and sponsored by General Motors Corporation (GM), and the U.S. Department of Energy (DOE). Following GM's Vehicle Development Process (VDP), HEVT established team goals that meet or exceed the competition requirements for EcoCAR in the design of a plug-in extended-range hybrid electric vehicle. The competition requires participating teams to improve and redesign a stock Vue XE donated by GM. The result of this design process is an Extended-Range Electric Vehicle (E-REV) that uses grid electric energy and E85 fuel for propulsion. The vehicle design is predicted to achieve an SAE J1711 utility factor corrected fuel consumption of 2.9 L(ge)/100 km (82 mpgge) with an estimated all electric range of 69 km (43 miles) [1].

This paper discusses the importance of vibration transmitted from the ground to the driver from the perspective of human whole-body vibration (WBV). The scope of analysis is to compare the main vehicle frequencies with those important from the human vibration health and comfort point of view. That was performed by mapping the vibration transmissibility present in different sub sections of the vehicle. The first is the transmissibility between the axles and the chassis rail, the following between the chassis rail and the cabin. The last would be between the cabin and the drivers' seat, although that was not possible from the acquisition point of view. The vehicles measured have mechanical suspension and elastomeric cabin coupling. It is known that all suspension systems in vehicle are highly nonlinear, although here linear dynamic analysis methods were used.

The present study introduces a proposal to improve the longitudinal performance of a land vehicle through the adoption of an unusual traction control system. The system is capable of improving the transfer of engine power to the ground and reduces the complexity of the task being performed by the driver. High-performance vehicles are able to achieve high levels of longitudinal acceleration and, sometimes, the power excess leads to the spinoff of the drive wheels, which decrease the ability of the tires to generate force, and consequently the vehicle acceleration. The proposed system acts in addition with the motor control, through the derivation of the motor speed signal, and its control by comparison with a predefined value. The control can delay or even suppress the ignition of the engine. Thus, the rate at which the engine gains speed, and consequently, the rate at which the vehicle accelerates, is limited.

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2009 - 2011 EcoCAR: The NeXt Challenge Advanced Vehicle Technology Competition series organized by Argonne National Lab (ANL), and sponsored by General Motors Corporation (GM), and the U.S. Department of Energy (DOE). Following GM's Vehicle Development Process (VDP), HEVT established team goals that meet or exceed the competition requirements for EcoCAR in the design of a plug-in extended range hybrid electric vehicle. The competition requires participating teams to re-engineer a stock crossover utility vehicle donated by GM. The result of this design process is an Extended Range Electric Vehicle (EREV) that uses grid electric energy and E85 fuel for propulsion. The vehicle design has achieved an SAE J1711 utility factor corrected fuel consumption of 2.9 L(ge)/100 km (82 mpgge) with an all-electric range of 87 km (54 miles) [1].

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2012 - 2014 EcoCAR 2: Plugging in to the Future Advanced Vehicle Technology Competition series organized by Argonne National Lab (ANL), and sponsored by General Motors Corporation (GM), and the U.S. Department of Energy (DOE). The goals of the competition are to reduce well-to-wheel (WTW) petroleum energy consumption, WTW greenhouse gas and criteria emissions while maintaining vehicle performance, consumer acceptability and safety. Following the EcoCAR 2 Vehicle Development Process (VDP), HEVT will design, build, and refine an advanced technology vehicle over the course of the three year competition using a 2013 Chevrolet Malibu donated by GM as a base vehicle. In year 1 of the competition, HEVT has designed a powertrain to meet and exceed the goals of the competition.

The Hybrid Electric Vehicle Team of Virginia Tech participated in the three-year EcoCAR Advanced Vehicle Technology Competition organized by Argonne National Laboratory, and sponsored by General Motors and the U.S. Department of Energy. The team established goals for the design of a plug-in, range-extended hybrid electric vehicle that meets or exceeds the competition requirements for EcoCAR. The challenge involved designing a crossover SUV powertrain to reduce fuel consumption, petroleum energy use, regulated tailpipe emissions, and well-to-wheel greenhouse gas emissions. To interface with and control the hybrid powertrain, the team added a Hybrid Vehicle Supervisory Controller, which enacts a torque split control strategy. This paper builds on an earlier paper [1] that evaluated the petroleum energy use, criteria tailpipe emissions, and greenhouse gas emissions of the Virginia Tech EcoCAR vehicle and control strategy from the 2nd year of the competition.

The Hybrid Electric Vehicle Team (HEVT) of Virginia Tech is participating in the 2011-2014 EcoCAR 2 competition in which the team is tasked with re-engineering the powertrain of a GM donated vehicle. The primary goals of the competition are to reduce well to wheels (WTW) petroleum energy use (PEU) and reduce WTW greenhouse gas (GHG) and criteria emissions while maintaining performance, safety, and consumer acceptability. To meet these goals HEVT has designed a series parallel plug-in hybrid electric vehicle (PHEV) with multiple modes of operation. This paper will first cover development of the control system architecture with a dual CAN bus structure to meet the requirements of the vehicle architecture. Next an online optimization control strategy to minimize fuel consumption will be developed. A simple vehicle plant model will then be used for software-in-the-loop (SIL) testing to improve fuel economy.

Heavy-vehicle event data recorders (HVEDRs) provide a source of temporal vehicle data just prior to, during, and for a short period after, an event. In the 1990s, heavy-vehicle (HV) engine manufacturers expanded the capabilities of engine control units (ECU) and engine control modules (ECM) to include the ability to record and store small amounts of parametric vehicle data. This advanced capability has had a significant impact on vehicle safety by helping law enforcement, engineers, and researchers reconstruct events of a vehicle crash and understand the details surrounding that vehicle crash. Today, EDR technologies have been incorporated into a wide range of heavy vehicle (HV) safety systems (e.g., crash mitigation systems, air bag control systems, and behavioral monitoring systems). However, the adoption of EDR technologies has not been uniform across all classes of HVs or their associated vehicle systems.

The Hybrid Electric Vehicle Team (HEVT) of Virginia Tech has achieved the Year 2 goal of producing a 65% functional mule vehicle suitable for testing and refinement, while maintaining the series-parallel plug-in hybrid architecture developed during Year 1. Even so, further design and expert consultations necessitated an extensive redesign of the rear powertrain and front auxiliary systems packaging. The revised rear powertrain consists of the planned Rear Traction Motor (RTM), coupled to a single-speed transmission. New information, such as the dimensions of the high voltage (HV) air conditioning compressor and the P2 motor inverter, required the repackaging of the hybrid components in the engine bay. The P2 motor/generator was incorporated into the vehicle after spreading the engine and transmission to allow for the required space.

The aim of this work is to present the preliminary configuration design studies for an unmanned, lightweight (less than 15 kg), supersonic research aircraft. The studies comprise the aircraft typical mission, the aerodynamic and structural arrangement, preliminary performance, as well as mass distribution. The aircraft, an Unmanned Air Vehicle, or “UAV”, is named as Pohox (“arrow” in Maxakali indian language). It is intended to be the flying test bed for a multicycle engine capable to provide thrust in subsonic, transonic and supersonic regimes. In order to provide validation of the analysis tools, flight performance characteristics of a known, high speed aircraft - North American X-15 - have been also evaluated and compared with the available flight test data. The present analysis is an important step towards the aircraft detailed definition. And the features associated with the configuration obtained are good indications of the technical feasibility of this supersonic UAV.

The significance and the number of vehicle safety features enabled via connectivity continue to increase. OnStar, with its automatic airbag notification, was one of the first vehicle safety features that demonstrate the enhanced safety benefits of connectivity. Vehicle connectivity benefits have grown to include remote software updates, data analytics to aid with preventative maintenance and even to theft prevention and recovery. All of these services require available and reliable connectivity. However, except for the airbag notification, none have strict latency requirements. For example, software updates can generally be postponed till reliable connectivity is available. Data required for prognostic use cases can be stored and transmitted at a later time. A new set of use cases are emerging that do demand continuous, reliable and low latency connectivity. For example, remote control of autonomous vehicles may be required in unique situations.

The Unmanned Ground Vehicle Competition is jointly sponsored by the SAE, the Association for Unmanned Vehicle Systems (AUVS), and Oakland University. College teams, composed of both undergraduate and graduate students, build autonomous vehicles that compete by navigating a 139 meter outdoor obstacle course. The course, which includes a sand pit and a ramp, is defined by painted continuous or dashed boundary lines on grass and pavement. The obstacles are arbitrarily placed, multi-colored plastic-wrapped hay bales. The vehicles must be between 0.9 and 2.7 meters long and less than 1.5 meters wide. They must be either electric-motor or combustion-engine driven and must carry a 9 kilogram payload. All computational power, sensing and control equipment must be carried on board the vehicle. The technologies employed are applicable in Intelligent Transportation Systems (ITS).

Dynamic “Game Theory” brings together different features that are keys to many situations in control design: optimization behavior, the presence of multiple agents/players, enduring consequences of decisions and robustness with respect to variability in the environment, etc. In previous studies, it was shown that vehicle stability can be represented by a cooperative dynamic/difference game such that its two agents (players), namely, the driver and the vehicle stability controller (VSC), are working together to provide more stability to the vehicle system. While the driver provides the steering wheel control, the VSC command is obtained by the Nash game theory to ensure optimal performance as well as robustness to disturbances. The common two-degree of freedom (DOF) vehicle handling performance model is put into discrete form to develop the game equations of motion. This study focus on the uncertainty in the inputs, and more specifically, the driver's steering input.

A crucial step to designing and building more efficient vehicles is modeling powertrain energy consumption. While accurate modeling is indeed key to effective and efficient design, a fundamental understanding of the powertrain and auxiliary systems that contribute to the energy consumption of a vehicle is equally as important. This paper presents a methodology that has been packaged into a tool, called VTool (short for Vehicle Tool), which can be used to estimate the energy consumption of a vehicle powertrain. The method is intrinsically designed to foster understanding of the vehicle powertrain as it relates to energy consumption and losses while still providing reasonably accurate results. This paper briefly explains the methodology of VTool and demonstrates the capability of VTool as a design tool by presenting 4 example exercises.

The pre-prototype development of a simulated rule-based hybrid energy management strategy for a 2019 Chevrolet Blazer RS converted parallel P4 full hybrid is presented. A vehicle simulation model is developed using component bench data and validated using EPA-reported dynamometer fuel economy test data. A combined Willans line model is proposed for the engine and transmission, with hybrid control rules based on efficiency-derived engine power thresholds. Algorithms are proposed for battery state of charge (SOC) management including engine loading and one pedal strategies, with battery SOC maintained within 20% to 80% safe limits and charge balanced behavior achieved. The simulated rule-based hybrid control strategy for the hybrid vehicle has an energy consumption reduction of 20% for the Hot 505, 3.6% for the HwFET, and 12% for the US06 compared to the stock vehicle.

Rapid adoption of battery electric vehicles means improving the energy consumption and energy efficiency of these new vehicles is a top priority. One method of accomplishing this is regenerative braking, which converts kinetic energy to electrical energy stored in the battery pack while the vehicle is decelerating. Coasting is an alternative strategy that minimizes energy consumption by decelerating the vehicle using only road load. A battery electric vehicle model is refined to assess regenerative braking, coasting, and other deceleration strategies. A road load model based on public test data calculates tractive effort requirements based on speed and acceleration. Bidirectional Willans lines are the basis of a powertrain model simulating battery energy consumption. Vehicle tractive and powertrain power are modeled backward from prescribed linear velocity curves, and the coasting trajectory is forward modeled given zero tractive power.

The influence of driver modeling and drive cycle target speed trace modification on vehicle dynamics within energy consumption simulations is studied. EPA dynamometer speed error criteria and the SAE J2951 Drive Quality Evaluation for Chassis Dynamometer Testing standard are applied to simulation outputs as proposed components of simulation validation, providing guidelines for acceptable vehicle speed outputs and allowing comparison of simulation results to reported EPA dynamometer test statistics. The combined effect of driver model tuning and drive cycle interpolation methods is investigated for the UDDS, HwFET and US06 drive cycles, with EPA-specified linearly interpolated speed trace and a PI controller driver as a baseline result.