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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 paper outlines a real-time hierarchical control allocation algorithm for multi-axle land vehicles with independent hub motor wheel drives. At the top level, the driver’s input such as pedal position or steering wheel position are interpreted into desired global state responses based on a reference model. Then, a locally linearized rigid body model is used to design a linear quadratic regulator that generates the desired global control efforts, i.e., the total tire forces and moments required track the desired state responses. At the lower level, an optimal control allocation algorithm coordinates the motor torques in such a manner that the forces generated at tire-road contacts produce the desired global control efforts under some physical constraints of the actuation and the tire/wheel dynamics. The performance of the proposed control system design is verified via simulation analysis of a 3-axle heavy vehicle with independent hub-motor drives.

Traditional Electronic Stability Control (ESC) for automobiles is usually accomplished through the use of estimated vehicle dynamics from simplified models that rely on parameters such as cornering stiffness that can change with the vehicle state and time. This paper proposes a different method for electronic stability control of oversteer by predicting the degree of instability in a vehicle. The algorithm is solely based on measurable response characteristics including lateral acceleration, yaw rate, speed, and driver steering input. These signals are appropriately conditioned and evaluated with fuzzy logic to determine the degree of instability present. When the “degree of instability” passes a certain threshold, the appropriate control action is applied to the vehicle in the form of differential yaw braking. Using only the measured response of the vehicle alleviates the problem of degraded performance when vehicle parameters change.

Over the last decade, tremendous amount of research and progress has been made towards developing smart technologies for autonomous vehicles such as adaptive cruise control, lane keeping assist, lane following algorithms, and decision-making algorithms. One of the fundamental objectives for the development of such technologies is to enable autonomous vehicles with the capability to avoid obstacles and maintain safety. Automobiles are real-world dynamical systems - possessing inertia, operating at varying speeds, with finite accelerations/decelerations during operations. Deployment of autonomy in vehicles increases in complexity multi-fold especially when high DOF vehicle models need to be considered for robust control. Model Predictive Control (MPC) is a powerful tool that is used extensively to control the behavior of complex, dynamic systems. As a model-based approach, the fidelity of the model and selection of model-parameters plays a role in ultimate performance.

Simultaneous Localization and Mapping (SLAM) algorithms are extensively utilized within the field of autonomous navigation. In particular, numerous open-source Robot Operating System (ROS) based SLAM solutions, such as Gmapping, Hector, Cartographer etc., have simplified deployments in application. However, establishing the accuracy and precision of these ‘out-of-the-box’ SLAM algorithms is necessary for improving the accuracy and precision of further applications such as planning, navigation, controls. Existing benchmarking literature largely focused on validating SLAM algorithms based upon the quality of the generated maps. In this paper, however, we focus on examining the localization accuracy of existing 2-dimensional LiDAR based indoor SLAM algorithms. The fidelity of these implementations is compared against the OptiTrack motion capture system which is capable of tracking moving objects at sub-millimeter level precision.

This paper presents a cohesive set of engine-in-the-loop (EIL) studies examining the use of hierarchical model-predictive control for fuel consumption minimization in a class-8 heavy-duty truck intended to be equipped with Level-1 connectivity/automation. This work is motivated by the potential of connected/automated vehicle technologies to reduce fuel consumption in both urban/suburban and highway scenarios. The authors begin by presenting a hierarchical model-predictive control scheme that optimizes multiple chassis and powertrain functionalities for fuel consumption. These functionalities include: vehicle routing, arrival/departure at signalized intersections, speed trajectory optimization, platooning, predictive optimal gear shifting, and engine demand torque shaping. The primary optimization goal is to minimize fuel consumption, but the hierarchical controller explicitly accounts for other key objectives/constraints, including operator comfort and safe inter-vehicle spacing.

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.

The emphasis on vehicle fuel economy and tailpipe emissions, coupled with a trend toward greater system functionally, has prompted automotive engineers to develop on-board control systems with increased requirements and complexity. Mainstream engine controllers regulate fuel, spark, and other subsystems using custom solutions that incorporate off-the-shelf hardware components. Although the digital processor core and the peripheral electronics may be similar, these controllers are targeted to fixed engine architectures which limit their flexibility across vehicle platforms. Moreover, additional software needs are emerging as electronics continue to permeate the ground transportation sector. Thus, automotive controllers will be required to assume increased responsibility while effectively communicating with distributed hardware modules.

This paper discusses a compliant link suspension concept developed for use on a high performance automobile. This suspension uses compliant or flexible members to integrate energy storage and kinematic guidance functions. The goal of the design was to achieve similar elasto-kinematic performance compared to a benchmark OEM suspension, while employing fewer components and having reduced mass and complexity, and potentially providing packaging advantages. The proposed suspension system replaces a control arm in the existing suspension with a ternary supported compliant link that stores energy in bending during suspension vertical motion. The design was refined iteratively by using a computational model to simulate the elasto-kinematic performance as the dimensions and attachment point locations of the compliant link were varied, until the predicted performance closely matched the performance of the benchmark suspension.

This paper proposes and compares torque distribution management strategies for vehicle stability control (VSC) of vehicles with independently driven wheels. For each strategy, the following feedback control variables are considered turn by turn: 1) yaw rate 2) lateral acceleration 3) both yaw rate and lateral acceleration. Computer simulation studies are conducted on the effects of road friction conditions, feedback controller gains, and a driver emulating speed controller. The simulation results indicated that all VSC torque management strategies are generally very effective in tracking the reference yaw rate and lateral acceleration of the vehicle on both dry and slippery surface conditions. Under the VSC strategies employed and the test conditions considered, the sideslip angle of the vehicle remained very small and always below the desired or target values.

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 functionality and performance of an internal combustion (spark or compression ignition) engine's thermal management system can be significantly enhanced through the application of mechatronics technology. The replacement of the conventional thermostat valve and mechanical coolant pump in the heating/cooling system by a servo-motor driven smart valve and variable flow pump permits powertrain control module regulated coolant flow through the engine block and radiator. In this paper, a dynamic mathematical model will be created for a 4.6L spark ignition engine to analyze various thermal management system architectures. The designs to be studied include the factory configuration, a smart valve upgrade, and the smart valve combined with a variable flow pump and radiator fan. Representative results are presented and discussed to demonstrate improvements in the engine warm-up time, temperature tracking, and component power consumption.

Thermal control systems for space application plant growth chambers offer unique challenges. The ability to control temperature and humidity independently gives greater flexibility for optimizing plant growth. Desired temperature and relative humidity range vary widely from 15°C to 35°C and 65% to 85% respectively. On top of all of these variables, the thermal control system must also be conservative in power and mass. These requirements to develop and test a robust thermal control system for space applications led to the design and development of the Environmental System Test Stand (ESTS) at NASA Johnson Space Center (JSC). The ESTS was designed to be a size constrained, environmental control system test stand with the flexibility to allow for a variety of thermal and lighting technologies. To give greater understanding to the environmental control system, the development of the ESTS included both mathematical models and the physical test stand.

The Waste and Hygiene Compartment will serve as the primary facility for metabolic waste management and personal hygiene on the United States segment of the International Space Station. The Compartment encloses the volume of two standard ISS racks and will be installed into Node 3 after launch inside a Multipurpose Logistics Module on the Space Shuttle. Long duration space flight requires a departure from the established hygiene and waste disposal practices employed on the Space Shuttle. This paper describes requirements and a conceptual design for the Waste and Hygiene Compartment that are both logistically practical and acceptable to the crew.

Research into increased capacity solid amine sorbents has found a candidate (SA9T) that will provide enough increase in cyclic carbon dioxide removal capacity to produce a fully redundant Regenerative Carbon Dioxide Removal System (RCRS). This system will eliminate the need for large quantities of backup LiOH, thus gaining critical storage space on board the shuttle orbiter. This new sorbent has shown an ability to package two fully redundant (four) sorbent beds together with their respective valves, fans and plumbing to create two operationally independent systems. The increase in CO2 removal capacity of the new sorbent will allow these two systems to fit within the envelope presently used by the RCRS. This paper reports on the sub-scale amine testing performed in support of the development effort. In addition, this paper will provide a preliminary design schematic of a fully redundant RCRS.

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.

A key component of an Advanced Life Support (ALS) system is the solid waste handling system. One of the most important data sets for determining what solid waste handling technologies are needed is a solid waste model. A preliminary solid waste model based on a six-person crew was developed prior to the 2000 Solid Waste Processing and Resource Recovery (SWPRR) workshop. After the workshop, comments from the ALS community helped refine the model. Refinements included better estimates of both inedible plant biomass and packaging materials. Estimates for Extravehicular Mobility Unit (EMU) waste, water processor brine solution, as well as the water contents for various solid wastes were included in the model refinement efforts. The wastes were re-categorized and the dry wastes were separated from wet wastes. This paper details the revised model as of the end of 2001. The packaging materials, as well as the biomass wastes, vary significantly between different proposed Mars missions.

The quantitative analysis of the food system for long-term space missions is a crucial factor for the comparison of different food plans and for the evaluation of the food system as part of the overall mission. Such analysis should include important factors such as nutrition, palatability, diet cycle length, and psychological issues related to food. This paper will give the details of a mathematical model that was developed during the first author's participation as a Summer Faculty Fellow at Johnson Space Center. The model includes nutrition, palatability, diet cycle length, and psychological issues as important components. The model is compatible with the Equivalent System Mass (ESM) metric previously developed as the Advance Life Support (ALS) Research and Technology Metric.

The International Space Station Waste Collector Subsystem Risk Mitigation Experiment (ISS WCS RME) was flown as the primary (Shuttle) WCS on Space Shuttle flight STS-104 (ISS-7A) in July 2001, to validate new design enhancements. In general, the WCS is utilized for collecting, storing, and compacting fecal & associated personal hygiene waste, in a zero gravity environment. In addition, the WCS collects and transfers urine to the Shuttle waste storage tank. All functions are executed while controlling odors and providing crew comfort. The ISS WCS previously flew on three Shuttle flights as the Extended Duration Orbiter (EDO) WCS, as it was originally designed to support extended duration Space Shuttle flights up to 30 days in length. Soon after its third flight, the Space Shuttle Program decided to no longer require 30 day extended mission duration capability and provided the EDO WCS to the ISS Program.