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Vehicle navigation in off-road environments is challenging due to terrain uncertainty. Various approaches that account for factors such as terrain trafficability, vehicle dynamics, and energy utilization have been investigated. However, these are not sufficient to ensure safe navigation of optionally manned ground vehicles that are prone to detection using thermal infrared (IR) seekers in combat missions. This work is directed towards the development of a vehicle IR signature aware navigation stack comprised of global and local planner modules to realize safe navigation for optionally manned ground vehicles. The global planner used A* search heuristics designed to find the optimal path that minimizes the vehicle thermal signature metric on the map of terrain’s apparent temperature. The local planner used a model-predictive control (MPC) algorithm to achieve integrated motion planning and control of the vehicle to follow the path waypoints provided by the global planner.

Improving vehicle response through advanced knowledge of traffic behavior can lead to large improvements in energy consumption for the single isolated vehicle. This energy savings across multiple vehicles can even be larger if they travel together as a cohort in harmonization. Additionally, if the vehicles have enough information about their immediate path of travel, and other vehicles’ in that path (and their respective critical forward-looking information), they can safely drive close enough to each other to share aerodynamic load. These energy savings can be upwards of multiple percentage points, and are dependent on several criteria. This analysis looks at criteria that contributes to energy savings for a cohort of vehicles in synchronous motion, as well as describes a study that allows for better understanding of the potential benefits of different types of cohorted vehicles in different platoon arrangements.

Robust autonomous navigation in unstructured environments is an unsolved problem and critical to the operation of autonomous military and rescue ground vehicles. Two-dimensional path planners operating on occupancy grids or costs maps can produce infeasible paths when the operational area includes complex terrain. Recently, sample-based path planners that plan on LiDAR-acquired point-cloud maps have been proposed. These approaches require no discretization of the operational area and provide direct pose estimation by modeling vehicle and terrain interaction. In this paper, we show that direct sample-based path planning on point clouds is effective and robust in unstructured environments. Robustness is demonstrated by completing a system parameter sensitivity analysis of the system in an Unreal simulation environment and partnered with field validation.

Traffic state identification is a key problem in intelligent transportation system. As a new technology, connected and automated vehicle can play a role of identifying traffic state with the installation of onboard sensors. However, research of lane level traffic state identification is relatively lacked. Identifying lane level traffic state is helpful to lane selection in the process of driving and trajectory planning. In addition, traffic state identification precision with low penetration of connected and automated vehicles is relatively low. To fill this gap, this paper proposes a novel method of identifying traffic state in the presence of connected and automated vehicles with low penetration rate. Assuming connected and automated vehicles can obtain information of surrounding vehicles’, we use the perceptible information to estimate imperceptible information, then traffic state of road section can be inferred.

While significant progress has been made in recent years to develop hybrid and battery electric vehicles for passenger car and light-duty applications to meet future fuel economy targets, the application of hybrid powertrains to heavy-duty truck applications has been very limited. The relatively lower energy and power density of batteries in comparison to diesel fuel and the operating profiles of most heavy-duty trucks, combine to make the application of hybrid powertrain for these applications more challenging. The high torque and power requirements of heavy-duty trucks over a long operating range, the majority of which is at constant cruise point, along with a high payback period, complexity, cost, weight and range anxiety, make the hybrid and battery electric solution less attractive than a conventional powertrain.

When a manual transmission (MT) powertrain is subjected to high speeds and high torques, the vehicle driveshaft, and other components experience an increase in stored potential energy. When the engine and driveshaft are decoupled during an up or down shift, the potential energy is released causing clunk during the shift event. The customer desires a smooth shift thus reduction of clunk will improve experience and satisfaction. In this study, a six-speed MT, rear-wheel-drive (RWD) passenger vehicle was used to experimentally capture acoustic and vibration data during the clunk event. To replicate the in-situ results, additional data was collected and analyzed for powertrain component roll and pitch. A lumped parameter model of key powertrain components was created to replicate the clunk event and correlate with test data. The lumped parameter model was used to modify clutch tip-out parameters, which resulted in reduced prop shaft oscillations.

A practical approach for evaluating and validating global system designs for Squeak and Rattle performance is proposed. Using simple slip and rattle models, actual sound and vibration data, and the fundamentals of audiological perception, analysis tools adapted from Chaos Theory are used to establish threshold levels of performance and identify system characteristics which are significant contributors to Squeak and Rattle. Focus on system design is maintained by using a simple rattle noise indicator and relating rattle events to levels of dynamic motion (acceleration, velocity, etc.). The threshold level is defined as the level of acceleration at which the system moves from a non-rattling state to a rattling state. The approach is demonstrated with a simple analytical model applied to an experimental structure under dynamic load.

Nitrites have long been added to heavy-duty coolant to inhibit iron cylinder liner corrosion initiated by cavitation. However, in heavy-duty use, nitrites deplete from the coolant, which then must be refortified using supplemental coolant additives (SCA's). Recently, carboxylates have also been found to provide excellent cylinder liner protection in heavy-duty application. Unlike nitrites, carboxylate inhibitors deplete slowly and thus do not require continual refortification with SCA's. In the present paper laboratory aging experiments shed light on the mechanism of cylinder liner protection by these inhibitors. The performance of carboxylates, nitrites and mixtures of the two inhibitors are compared. Results correlate well with previously published fleet data. Specifically, rapid nitrite and slow carboxylate depletion are observed. More importantly, when nitrite and carboxylates are used in combination, nitrite depletion is repressed while carboxylates deplete at a very slow rate.

The automotive industry is dramatically changing. Many automotive Original Equipment Manufacturers (OEMs) proposed new prototype models or concept vehicles to promote a green vehicle image. Non-traditional players bring many latest technologies in the Information Technology (IT) industry to the automotive industry. Typical vehicle’s characteristics became wider compared to those of vehicles a decade ago, and they include not only a driving range, mileage per gallon and acceleration rating, but also many features adopted in the IT industry, such as usability, connectivity, vehicle software upgrade capability and backward compatibility. Consumers expect the latest technology features in vehicles as they enjoy in using digital applications in laptops and mobile phones. These features create a huge challenge for a design of a new vehicle, especially for a human-machine-interface (HMI) system.

This paper studies the hardware-in-the-loop (HiL) design of a power-split hybrid electric vehicle (HEV) for the research of HEV lithiumion battery aging. In this paper, an electrochemical model of a lithium-ion battery pack with the characteristics of battery aging is built and integrated into the vehicle model of Autonomie® software from Argonne National Laboratory. The vehicle model, together with the electrochemical battery model, is designed to run in a dSPACE real-time simulator while the powertrain power distribution is managed by a dSPACE MicroAutoBoxII hardware controller. The control interface is designed using dSPACE ControlDesk to monitor the real-time simulation results. The HiL simulation results with the performance of vehicle dynamics and the thermal aging of the battery are presented and analyzed.

China has become the world’s largest vehicle market in terms of sales volume. Automobiles sales keep growing in recent years despite the declining economic growth rate. Due to the increasing attention given to the environmental impact, more stringent emission regulations are being drafted to control traditional internal combustion engine emissions. In order to reduce vehicle emissions, environmentally-friendly new-energy vehicles, such as electric vehicles and plug-in hybrid vehicles, are being promoted by government policies. The Chinese government plans to boost sales of new-energy cars to account for about five percent of China’s total vehicle sales. It is well known that more electric and electronic components will be integrated into a vehicle platform during vehicle electrification.

Elastomers are traditionally designed for use in applications that require specific mechanical properties. Unfortunately, these properties change with respect to many different variables including heat, light, fatigue, oxygen, ozone, and the catalytic effects of trace elements. When elastomeric mounts are designed for NVH use in vehicles, they are designed to isolate specific unwanted frequencies. As the elastomers age however, the desired elastomeric properties may have changed with time. This study looks at the variability seen in new vehicle engine mounts and how the dynamic properties change with respect to miles accumulated on fleet and durability test vehicles.

The role of mixture stratification on combustion rate has been investigated in a constant volume combustion vessel in which mixtures of different equivalence ratios can be added in a spatially and temporally controlled fashion. The experiments were performed in a regime of low fluid motion to avoid the complicating effects of turbulence generated by the injection of different masses of fluid. Different mixture combinations were investigated while maintaining a constant overall equivalence ratio and initial pressure. The results indicate that the highest combustion rate for an overall lean mixture is obtained when all of the fuel is contained in a stoichiometric mixture in the vicinity of the ignition source. This is the result of the high burning velocity of these mixtures, and the complete oxidation which releases the full chemical energy.

For competition in the 1998 FutureCar Challenge (FCC98), the University of Wisconsin - Madison FutureCar Team has designed and built a lightweight, charge sustaining, parallel hybrid electric vehicle by modifying a 1994 Mercury Sable Aluminum Intensive Vehicle (AIV), nicknamed the Aluminum Cow. The Wisconsin team is striving for a combined, FTP cycle gasoline-equivalent fuel economy of 21.3 km/L (50 mpg) and Ultra Low Emissions Vehicle (ULEV) federal emissions levels while maintaining the full passenger/cargo room, appearance, and feel of a full-size car. To reach these goals, Wisconsin has concentrated on reducing the overall vehicle weight. In addition to customizing the drivetrain, the team has developed a vehicle control strategy that both aims to achieve these goals and also allows for the completion of a reliable hybrid in a short period of time.

Catalytic converters have become a viable aftertreatment system for reducing emissions from on-highway diesel engines. This paper addresses the development and production qualification of a catalytic converter. The testing programs that were utilized to qualify the converter system for production included emissions performance, emissions durability, physical durability, and field test programs. This paper reports on the specific tests that were utilized for the emissions performance and emissions durability testing programs. An explanation on the development of an accelerated durability test program is also included. The physical durability section of the paper discusses the development and execution of laboratory bench tests to insure the catalytic converter/muffler maintains acceptable physical integrity.

Recreational Ecological Vehicle (REV) 74 was an intercollegiate All Terrain Vehicle (ATV) design competition organized by the Milwaukee and Cincinnati Sections of SAE. Students from six colleges built ATV's to compete May 30-June 1, 1974 at Michigan Technological University's Keweenaw Research Center test course. Competing categories of noise level, destructiveness to terrain and a 25 mile race over land and water are discussed from the viewpoint of the technical rules and as to the actual course involved with the competition. Michigan Tech designed and built a 4 wheel steer-4 wheel hydrostatic drive ATV for REV-74. This paper provides a detailed design description of the Michigan Tech vehicle along with a review of several production ATV designs and their specifications. Finally, a report of the results of REV-74 is presented.

A modular and scalable Dense Medium Plasma Water Purification Reactor was developed, which uses atmospheric-pressure electrical discharges under water to generate highly reactive species to break down organic contaminants and microorganisms. Key benefits of this novel technology include: (i) extremely high efficiency in both decontamination and disinfection; (ii) operating continuously at ambient temperature and pressure; (iii) reducing demands on the containment vessel; and (iv) requiring no consumables. This plasma based technology was developed to replace the catalytic reactor being used in the planned International Space Station Water Processor Assembly.

A study was performed that takes into account both turbulence and chemical kinetic effects in the numerical simulation of diesel engine combustion in order to better understand the importance of their respective roles at changing operating conditions. An approach was developed which combines the simplicity and low computational and storage requests of the laminar-and-turbulent characteristic-time model with a detailed combustion chemistry model based on well-known simplified mechanisms. Assuming appropriate simplifications such as steady state or equilibrium for most of the radicals and intermediate species, the kinetics of hydrocarbons can be described by means of three overall steps. This approach was integrated in the KIVA-II code. The concept was validated and applied to a single-cylinder, heavy-duty engine. The simulation covers a wide range of operating conditions.

The advancement in embedded systems and positional accuracy with base station GPS modules created opportunity to develop high performance autonomous ground vehicles. However, the development of vehicle model and making accurate state estimations play vital role in reducing the cross track error. The present research focus on developing Linear Quadratic Gaussian (LQG) with Kalman estimator for autonomous ground vehicle to track various routes, that are made with the series of waypoints. The model developed in the LQG controller is a kinematic bicycle model, which mimics 1/5th scale truck. Further, the cubic spline fit has been used to connect the waypoints and generate the continuous desired/target path. The testing and implementation has been done at APS labs, MTU on the mentioned vehicle to study the performance of controller. Python has been used for simulations, controller coding and interfacing the sensors with controller.

An experimental investigation of the spectral characteristics of turbulent flow in a scale model of a high pressure diesel fuel injector nozzle hole has been conducted. Instantaneous velocity measurements were made in a 50X transparent model of one hole of an injector nozzle using an Aerometrics Phase/Doppler Particle Analyzer (PDPA) in the velocity mode. Turbulence spectra were calculated from the velocity data using the Lomb-Scargle method. Injector hole length to diameter ratio (L/D) values of 1.3, 2.4, 4.9, and 7.7 and inlet radius to diameter ratio (R/D) values of approximately 0 and 0.3 were investigated. Results were obtained for a steady flow average Reynolds number of 10,500, which is analogous to a fuel injection velocity of 320 m/s and a sac pressure of approximately 67 MPa (10,000 psi). Turbulence time frequency spectra were obtained for significant locations in each geometry, in order to determine how geometry affects the development of the turbulent spectra.