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Predicting fuel economy during early stages of concept development or feasibility study for a new type of powertrain configuration is an important key factor that might affect the powertrain configuration decision to meet CAFE standards. In this paper an efficient model has been built in order to evaluate the fuel economy for a new type of charge sustaining series hybrid vehicle that uses a Genset assembly (small 2 cylinders CNG fueled engine coupled with a generator). A first order mathematical model for a Li-Ion polymer battery is presented based on actual charging /discharging datasheet. Since the Genset performance data is not available, normalized engine variables method is used to create powertrain performance maps. An Equivalent Consumption Minimization Strategy (ECMS) has been implemented to determine how much power is supplied to the electric motor from the battery and the Genset.

Hybrid vehicle embedded systems and payloads require progressively more accurate and versatile thermal control mechanisms and strategies capable of withstanding harsh environments and increasing power density. The division of the cargo and passenger compartments into convective thermal zones which are independently managed can lead to a manageable temperature control problem. This study investigates the performance of a Peltier-effect thermoelectric zone cooling system to regulate the temperature of target objects (e.g., electronic controllers, auxiliary computer equipment, etc) within ground vehicles. Multiple thermoelectric cooling modules (TEC) are integrated with convective cooling fans to provide chilled air for convective heat transfer from a robust, compact, and solid state device. A series of control strategies have been designed and evaluated to track a prescribed time-varying temperature profile while minimizing power consumption.

This research proposes a control system for Spark Ignition (SI) engines with external Exhaust Gas Recirculation (EGR) based on model predictive control and a disturbance observer. The proposed Economic Nonlinear Model Predictive Controller (E-NMPC) tries to minimize fuel consumption for a number of engine cycles into the future given an Indicated Mean Effective Pressure (IMEP) tracking reference and abnormal combustion constraints like knock and combustion variability. A nonlinear optimization problem is formulated and solved in real time using Sequential Quadratic Programming (SQP) to obtain the desired control actuator set-points. An Extended Kalman Filter (EKF) based observer is applied to estimate engine states, combining both air path and cylinder dynamics. The EKF engine state(s) observer is augmented with disturbance estimation to account for modeling errors and/or sensor/actuator offset.

This paper argues the importance of engineering heuristics and introduces an educational data-driven tool to help novice engineers develop their engineering heuristics more effectively. The main objective in engineering practice is to identify opportunities for improvement and apply methods to effect change. Engineers do so by applying ‘how to’ knowledge to make decisions and take actions. This ‘how to’ knowledge is encoded in engineering heuristics. In this paper, we describe a tool that aims to provide heuristic knowledge to users by giving them insight into heuristics applied by experts in similar situations. A repository of automotive data is transformed into a tool with powerful search and data visualization functionalities. The tool can be used to educate novice automotive engineers alongside the current resource intensive practices of teaching engineering heuristics through social methods such as an apprenticeship.

Novice drivers are often ill-equipped to safely operate a motor vehicle due to their limited repertoire of skills and experiences. However, automotive simulation tools can be applied to better educate young drivers for a number of common driving scenarios. In this paper, the Clemson Automotive Training System (CATS) will be presented to educate and train novice drivers to safely operate four wheel passenger vehicles on paved roadways. A portable automotive simulator can be programmed to emulate a variety of high-crash rate scenarios and roadway geometries. Drivers receive instructions regarding proper driving techniques and behaviors with an opportunity to practice the given vehicle maneuver. An on-line evaluation methodology has been designed to analyze the drivers' capabilities at handling these roadway events. First, a pre-simulation questionnaire evaluates their basic understanding of everyday driving situations.

Current military operations in Iraq and Afghanistan are unique because the battlefield can be described as a non-linear, asymmetrical environment. Units operate in zones that are susceptible to enemy contact from any direction at any time. The response to these issues has been the addition of add-on armor to HMMWV's and other tactical vehicles. The retro-fitting of armor to these vehicles has resulted in many accidents due to rollover and instability. The goal of this paper is to determine possible causes of the instability and rollover of up-armored tactical vehicles and to develop simulation tools that can analyze the steady-state and transient dynamics of the vehicles. Models and simulations include a steady-state rollover scenario, analysis of understeer gradient, and a transient handling analysis that uses models of both a human driver and a vehicle to analyze vehicle response to an obstacle avoidance maneuver.

With the dramatic increase in vehicle technology, the availability of a wide range of powertrains, and the development of advanced driver assistant systems (ADAS), instrument cluster interfaces have become more complex, increasing the demand on drivers. Understanding the needs and preferences of a diverse group of drivers is essential for the development of digital instrument cluster interfaces that improve driver’s understanding of critical information about the vehicle. This study investigated drivers’ understanding and preferences related to powertrain and ADAS symbols presented on instrument clusters. Participants answered questions that evaluated nine symbol’s comprehension, familiarity, and helpfulness. Then, participants were presented with information from the owner’s manual for each symbol and responded if the information changed their understanding of the symbol.

Collaborative robots are more and more used in smart manufacturing because of their capability to work beside and collaborate with human workers. With the deployment of these robots, manufacturing tasks are more inclined to be accomplished by multiple humans and multiple robots (MH-MR) through teaming effort. In such MH-MR collaboration scenarios, the task distribution among the multiple humans and multiple robots is very critical to efficiency. It is also more challenging due to the heterogeneity of different agents. Existing approaches in task distribution among multiple agents mostly consider humans with assumed or known capabilities. However human capabilities are always changing due to various factors, which may lead to suboptimal efficiency. Although some researches have studied several human factors in manufacturing and applied them to adjust the robot task and behaviors.

This paper is a review of turbulence models and computational methods that have been produced at Clemson University's Advanced Computational Research Laboratory. The goal of the turbulence model development has been to create physics-based models that are economically feasible and can be used in a competitive environment, where turnaround time is a critical factor. Given this goal, all of the work has been focused on Reynolds-Averaged Navier-Stokes (RANS) simulations in the eddy-viscosity framework with the majority of the turbulence models having three transport equations in addition to mass, momentum, and energy. Several areas have been targeted for improvement in turbulence modeling for complex flows such as those found in motorsports aerodynamics: the effects of streamline curvature and rotation on the turbulence field, laminar-turbulent transition, and separated shear layer rollup and breakdown.

The first concept and early experiments of a mechanical counter pressure (MCP) spacesuit were published by Webb in the late 1960's. MCP provides an alternative approach to the conventional full pressure suit that bears some significant advantages, such as increased mobility, dexterity, and tactility. The presented ongoing research provides a thorough investigation of the physiological effect of mechanical counter pressure applied onto the human skin. In this study, we investigated local microcirculatory effects produced with negative and positive ambient pressure on the lower body as a preliminary study for a lower body garment. The data indicates that the positive pressure was less tolerable than negative pressure. Lower body negative and positive pressure cause various responses in skin blood flow due to not only blood shifts but also direct exposure to pressure differentials.

Understanding the effects of tire and vehicle properties on the rollover propensity of tractor semi-trailer trucks is essential. The major objective of the project described by this paper was to develop a simplified computational tool that can be used to understand and predict the effects of various tire characteristics and truck design parameters on rollover under steady cornering and non-tripped conditions. In particular, this tool may be used to help understand the basic mechanisms governing rollover propensity of trucks equipped with New Generation Wide Single tires as contrasted with conventional tires. Effects of tire flexibility, roll-compliant suspensions, fifth - wheel lash and nonlinear suspension characteristics are included in the model and are presented below. Design parameter data used as input to the model were obtained from Michelin Americas Research and Development Corporation.

Shorter development times in the automotive industry are leading to the increased use of computer simulation in the vehicle design cycle to pre-optimize vehicle concepts. The focus of the work presented in this study is vehicle dynamic performance in different driving maneuvers. More specifically this paper presents a methodology for simulation-based parameter design of vehicles for excellent performance in multiple maneuvers. The model used in the study consists of eight degrees-of-freedom and has been validated previously. The vehicle data used is for a commercially available vehicle. A number of different driving scenarios (maneuvers) based on ISO standards for transient dynamic behavior are implemented and performance indices are calculated for each individual maneuver considered. Vehicle performance is assessed based on the performance indices.

Vehicle dynamics simulation is one of the newest and most valuable technologies being applied in the racing world today. Professional designers and race teams are investing heavily to test and improve the dynamics of their suspension systems through this new technology. This paper discusses the testing of one of Clemson University's most recent Formula SAE racecars on a seven-poster vehicle dynamics simulator; commonly known as a “shaker rig.” Testing of the current dampers using a shock dynamometer was conducted prior to testing and results are included for further support of conclusions. The body of the paper is a discussion of the setup and testing procedures involved with the dynamic simulator. The results obtained from the dynamic simulator tests are then analyzed in conjunction with the shock dynamometer results. Conclusions are formed from test results and methods for future improvements to be applied in Formula SAE racing are suggested.

In the next 20 years fully autonomous vehicles are expected to be in the market. The advance on their development is creating paradigm shifts on different automotive related research areas. Vehicle interiors design and human vehicle interaction are evolving to enable interaction flexibility inside the cars. However, most of today’s vehicle manufacturers’ autonomous car concepts maintain the steering wheel as a control element. While this approach allows the driver to take over the vehicle route if needed, it causes a constraint in the previously mentioned interaction flexibility. Other approaches, such as the one proposed by Google, enable interaction flexibility by removing the steering wheel and accelerator and brake pedals. However, this prevents the users to take control over the vehicle route if needed, not allowing them to make on-route spontaneous decisions, such as stopping at a specific point of interest.

Despite the growing acceptance of driver education programs, there remains a class of unpredictable and dangerous vehicle situations for which very little training or education is offered. Included in this list is a condition called run-off-the-road (ROR) which occurs when the wheels of the vehicle leave the paved surface of the road and begin to travel on the lower friction surfaces of the shoulder or side of the road. Unsuccessful recovery from ROR contributes to an overwhelming percentage of motorized vehicle crash fatalities and injuries. Most present solutions involve roadway infrastructure management and driver assistance systems. While these solutions have contributed varying amounts of success to the ROR problem, they remain limited as they do not directly address the critical cause of ROR crashes which is driver performance errors.

Decreasing the propensity for rollover during steady state cornering of tractor semi-trailers is a key advantage to the trucking industry. This will be referred to as “increasing the lateral stability during steady state cornering” and may be accomplished by changes in design and loading variables which influence the behavior of a vehicle. To better understand the effects of such changes, a computer program was written to optimize certain design variables and thus maximize the lateral acceleration where an incipient loss of lateral stability occurs. The vehicle model used in the present investigation extends that developed by Law [1] and presented in Law and Janajreh [2]. The original model included the effects of tire flexibility, nonlinear roll-compliant suspensions, and fifth wheel lash. This model was modified to include (a) additional effects of displacement due to both lateral and vertical tire flexibility, and (b) provisions for determining “off-tracking”.

A safe driver program has been established through a public-private partnership. This program targets novice drivers and uses a combination of classroom and in-vehicle training exercises to address critical driver errors known to lead to crashes. Students participate in four modules: braking to learn proper stopping technique, obstacle avoidance / reaction time to facilitate proper lane selection and collision avoidance, tailgating to learn about following distances, and loss of control to react appropriately when a vehicle is about to become laterally unstable. Knowledge pre and posttests are also administered at the start and end of the program. Students' in-vehicle driving performance are evaluated by instructors as well as recorded by onboard data acquisition units. The data has been evaluated with objective and subjective grading rubrics. The 70 participants in three classes used as a case study achieved an average skill score of 83.93/100.

Understanding the parameters which influence the tendency for a heavy truck to exhibit rollover is of paramount importance to the trucking industry. Multiple parameters influence the vehicle’s motion, and the ability to determine how each affects the vehicle as a system would be an indispensable tool for the design of such vehicles. To be able to perform such predictions and analysis, models and a computer simulation were created to allow the examination of changes in design parameters in such vehicles. The vehicle model was originally developed by Law [1] and presented in Law and Janajreh [2]. The model was extended further by Lawson [3, 4] to include (a) the effects of the torsional compliance of both the tractor and trailer, and (b) tanker trailers with various levels of liquid fill. In the present paper, both the tractor and trailer compliances were studied independently to determine their influences on the rollover stability of the vehicle.

Electrified transportation has received significant interest recently because of sustainable and clean energy goals. However, the degradation of electrical components such as energy storage systems raises system reliability and economic concerns. In this paper, a prognostic-based control strategy is proposed for hybrid electric vehicles (HEVs) to abate the degradation of energy systems. Degradation forecasting models of electrical components are developed to predict their degradation paths. The predicted results are then used to control HEVs in order to reduce the degradation of components.

As powertrain hybridization technologies are becoming popular, their application for heavy-duty military vehicles is drawing attention. An intelligent design and operation of the energy management system (EMS) is important to ensure that hybrid military vehicles can operate efficiently, simultaneously maximize fuel economy and minimize monetary cost, while successfully completing mission tasks. Furthermore, an integrated EMS framework is vital to ensure a functional vehicle power system (VPS) to survive through critical missions in a highly stochastic environment, when needed. This calls for situational awareness and dynamic system reconfiguration capabilities on-board of the military vehicle. This paper presents a new energy management and control (EMC) framework based on holistic situational awareness (SA) and dynamic reconfiguration of the VPS.