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Variant modeling techniques have been developed to allow systems engineers to model multiple similar variants in a product line as a single variant model. In this paper, we expand on this past work to explore the extent to which variant modeling in SysML can be applied to a broad range of dissimilar systems, covering the entire domain of ground vehicles, in single reference architecture model. Traditionally, a system’s structure is decomposed into subsystems and components. However, this method is found to be ineffective when modeling variants that are functionally similar but structurally different. We propose to address this challenge by first decomposing the system not only by subsystem but also by high-level function. This pattern is particularly useful for situations where two variants perform the same function, but one variant performs the function using one subsystem, whereas the other variant performs the same function using one or more different subsystems.

Most studies on supervisory controllers of hybrid electric vehicles consider only fuel economy in the objective function. Taking into consideration the importance of the energy storage system health and its impact on the vehicle’s functionality, cost, and warranty, recent studies have included battery degradation as the second objective function by proposing different energy management strategies and battery life estimation methods. In this paper, a rule-based supervisory controller is proposed that splits the torque demand based not only on fuel consumption, but also on the battery capacity fade using the concept of severity factor. For this aim, the severity factor is calculated at each time step of a driving cycle using a look-up table with three different inputs including c-rate, working temperature, and state of charge of the battery. The capacity loss of the battery is then calculated using a semi-empirical capacity fade model.

With recent advances in electric vehicles, there is a plethora of powertrain topologies and components available in the market. Thus, the performance of electric vehicles is highly sensitive to the choice of various powertrain components. This paper presents a multi-objective optimization model that can optimally select component sizes for batteries, supercapacitors, and motors in regular passenger battery-electric vehicles (BEVs). The BEV topology presented here is a hybrid BEV which consists of both a battery pack and a supercapacitor bank. Focus is placed on optimal selection of the battery pack, motor, and supercapacitor combination, from a set of commercially available options, that minimizes the capital cost of the selected power components, the fuel cost over the vehicle lifespan, and the 0-60 mph acceleration time. Available batteries, supercapacitors, and motors are from a market survey.

This paper proposes a novel 1-ϕ, Cuk based on-board electric vehicle (EV) charger with least power components. The proposed EV charger has a special feature to achieve power factor correction (PFC) at AC grid without requirement of the grid voltage and current sensors which cuts the cost and increases the power density of the EV charger along with robustness to noise. The automatic PFC at AC grid is accomplished by operating the output DC inductor in discontinuous conduction mode (DCM). The proposed EV charger necessitates a minimal number of power components for positive and negative half cycles of AC grid which improves the overall efficiency of the system. This is possible due to the combination of inverting and non-inverting Cuk converters are used for each half cycle of the AC grid. Further, the presence of output inductor in the EV charger reduces the ripples in the output current which is not common with all the existing chargers in the literature.

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.

Barriers are commonly used on roadways to separate and to protect against vehicles traveling in opposing directions from possible head-on collisions. However, these barriers may interfere with wildlife passage such that animals become trapped on the road. Typically, small animals cannot find safe passage across all traffic lanes due to the presence of solid barriers and eventually die after being hit by a vehicle. The occurrence of animal-to-vehicle collisions also presents a dangerous scenario for motorists as a driver may intuitively swerve to avoid hitting the animal. In this paper, a redesigned Jersey style barrier, named the Clemson smart portal, will be presented and discussed. This roadway barrier features a portal for small animal travel, along with a mechatronic-based warning system to notify drivers of animal passage.

Fuel efficiency improvement in automobiles has been a topic of great interest over the past few years, especially with the introduction of the new CAFE 2025 standards. Although there are multiple ways of improving the fuel efficiency of an automobile, lightweighting is one of the most common approaches taken by many automotive manufacturers. Lightweighting is even more significant in electric vehicles as it directly affects the range of the vehicle. Amidst this context of lightweighting, the use of composite materials as alternatives to metals has been proven in the past to help achieve substantial weight reduction. The focus of using composites for weight reduction has however been typically limited to major structural components, such as BiW and closures, due to high material costs. Secondary structural components which contribute approximately 30% of the vehicle weight are usually neglected by these weight reduction studies.

Designing an efficient cooling system with low power consumption is of high interest in the automotive engineering community. Heat generated due to the propulsion system and the on-board electronics in ground vehicles must be dissipated to avoid exceeding component temperature limits. In addition, proper thermal management will offer improved system durability and efficiency while providing a flexible, modular, and reduced weight structure. Traditional cooling systems are effective but they typically require high energy consumption which provides motivation for a paradigm shift. This study will examine the integration of passive heat rejection pathways in ground vehicle cooling systems using a “thermal bus”. Potential solutions include heat pipes and composite fibers with high thermal properties and light weight properties to move heat from the source to ambient surroundings.

Autonomous vehicles have the potential to provide mobility to individuals who experience transportation disadvantages due to the inability to drive as a result of physical, cognitive or visual limitations/impairments as well as able-bodied individuals with no/limited desire to drive. Individuals who do not have easy access to transportation have social, academic, health, and career disadvantages in comparison to their peers. Fully autonomous vehicles have the potential to offer mobility solutions to these individuals. A user-centered design approach was utilized by a multidisciplinary team of engineers, human factors specialists, and designers to develop future vehicle features for a broad range of users.

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.

This paper describes the development and simulation of a voice and pointing gesture interaction system for on-route update of autonomous vehicles’ path. The objective of this research is to provide users of autonomous vehicles a human vehicle interaction mode that enables them to make and communicate spontaneous decisions to the autonomous car, modifying its pre-defined autonomous route in real-time. For example, similar to giving directions to a taxi driver, a user will be able to tell the car «Stop there» or «Take that exit». In this way, the user control/spontaneity vs interaction flexibility dilemma that current autonomous vehicle concepts have, could be solved, potentially increasing the user acceptance of this technology. The system was designed following a level structured state machine approach. The simulations were developed using MATLAB and VREP, a robotics simulation platform, which has accurate vehicle and sensor models.

Access control enforces security policies for controlling critical resources. For V2X (Vehicle to Everything) autonomous military vehicle fleets, network middleware systems such as ROS (Robotic Operating System) expose system resources through networked publisher/subscriber and client/server paradigms. Without proper access control, these systems are vulnerable to attacks from compromised network nodes, which may perform data poisoning attacks, flood packets on a network, or attempt to gain lateral control of other resources. Access control for robotic middleware systems has been investigated in both ROS1 and ROS2. Still, these implementations do not have mechanisms for evaluating a policy's consistency and completeness or writing expressive policies for distributed fleets. We explore an RBAC (Role-Based Access Control) mechanism layered onto ROS environments that uses local permission caches with precomputed truth tables for fast policy evaluation.

The Advanced Inflatable Airlock (AIA) System is currently being developed for the 2nd Generation Reusable Launch Vehicle (RLV). The objective of the AIA System is to greatly reduce the cost associated with performing extravehicular activity (EVA) from the RLV by reducing launch weight and volume from previous hard airlock systems such as the Space Shuttle and Space Station airlocks. The AIA System builds upon previous technology from the TransHab inflatable structures project, from Space Shuttle and Space Station Airlock systems, and from terrestrial flexible structures projects. The AIA system design is required to be versatile and capable of modification to fit any platform or vehicle needing EVA capability. This paper discusses the AIA conceptual design and key features that will help meet the 2nd Generation RLV program goals of reduced cost and program risk.

This paper describes a computational and experimental effort to document the detailed flow field around a pickup truck. The major objective was to benchmark several different computational approaches through a series of validation simulations performed at Clemson University (CU) and overseen by those performing the experiments at the GM R&D Center. Consequently, no experimental results were shared until after the simulations were completed. This flow represented an excellent test case for turbulence modeling capabilities developed at CU. Computationally, three different turbulence models were employed. One steady simulation used the realizable k-ε model. The second approach was an unsteady RANS simulation, which included a turbulence closure model developed in-house. This simulation captured the unsteady shear layer rollup and breakdown over the front of the hood that was expected and seen in the experiments but unattainable with other off-the-shelf turbulence models.

Automotive and truck manufacturers are introducing electric propulsion systems into their ground vehicles to reduce fossil fuel consumption and harmful tailpipe emissions. The mobility shift to electric motors requires a compact thermal management system that can accommodate heat dissipation demands with minimum energy consumption in a confined space. An innovative cooling system design, emphasizing passive cooling methods coupled with a small liquid system, using a thermal bus architecture has been explored. The laboratory experiment features an emulated electric motor interfaced to a thermal cradle and multiple heat rejection pathways to evaluate the transfer of generated heat to the ambient surroundings. The thermal response of passive (e.g., carbon fiber, high thermal conductivity material, thermosyphon) and active cooling systems are investigated for two operating scenarios.

This paper details the concept of using an exergy-based method as a thermal design methodology tool for integrated aircraft thermal systems. An exergy-based approach was applied to the design of an environmental control system (ECS) of an advanced aircraft. Concurrently, a traditional energy-based approach was applied to the same system. Simplified analytical models of the ECS were developed for each method and compared to determine the validity of using the exergy approach to facilitate the design process in optimizing the overall system for a minimum gross takeoff weight (GTW). The study identified some roadblocks to assessing the value of using an exergy-based approach. Energy and exergy methods seek answers to somewhat different questions making direct comparisons awkward. Also, high entropy generating devices can dominate the design objective of the exergy approach.

The deployment of autonomous vehicles in real-world scenarios requires thorough testing to ensure sufficient safety levels. Driving simulators have proven to be useful testbeds for assisted and autonomous driving functionalities but may fail to capture all the nuances of real-world conditions. In this paper, we present a snapshot of the design and evaluation using a Cooperative Adaptive Cruise Control application of virtual reality platform currently in development at our institution. The platform is designed so to: allow for incorporating live real-world driving data into the simulation, enabling Vehicle-in-the-Loop testing of autonomous driving behaviors and providing us with a useful mean to evaluate the human factor in the autonomous vehicle context.

Enhanced electric motor performance in transportation vehicles can improve system reliability and durability over rigorous operating cycles. The design of innovative heat rejection strategies in electric motors can minimize cooling power consumption and associated noise generation while offering configuration flexibility. This study investigates an innovative electric motor cooling strategy through bench top thermal testing on an emulated electric motor. The system design includes passive (e.g., heat pipes) cooling as the primary heat rejection pathway with supplemental conventional cooling using a variable speed coolant pump and radiator fan(s). The integrated thermal structure, “cradle”, transfers heat from the motor shell towards an end plate for heat dissipation to the ambient surroundings or transmission to an external thermal bus to remote heat exchanger.

Hybrid electric vehicles offer the advantages of reduced emissions and greater travel range in comparison to conventional and electric ground vehicles. Regardless of propulsion strategy, efficient cooling of electric motors remains an open challenge due to the operating cycles and ambient conditions. The onboard thermal management system must remove the generated heat so that the motors and other vehicle components operate within their designed temperature ranges. In this article, an integrated thermal structure, or cradle, is designed to efficiently transfer heat within the motor housing to the end plates for transmission to an external heat exchanger. A radial array of heat pipes function as an efficient thermal connector between the motor and heat connector, or thermal bus, depending on the configuration. Cooling performance has been evaluated for various driving cycles.

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.