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Substantial fuel economy improvements for light-duty automotive engines demand novel combustion strategies. Low temperature combustion (LTC) demonstrates potential for significant fuel efficiency improvement; however, control complexity is an impediment for real-world transient operation. Spark-assisted compression ignition (SACI) is an LTC strategy that applies a deflagration flame to generate sufficient energy to trigger autoignition in the remaining charge. Operating a practical engine with SACI combustion is a key modeling and control challenge. Current models are not sufficient for control-oriented work such as calibration optimization, transient control strategy development, and real-time control. This work describes the process and results of developing a fast-running control-oriented model for the autoignition phase of SACI combustion. A data-driven model is selected, specifically artificial neural networks (ANNs).

Driving inattention caused by drowsiness has been a significant reason for vehicle crash accidents, and there is a critical need to augment driving safety by monitoring driver drowsiness behaviors. For real-time drowsy driving awareness, we propose a vision-based driver drowsiness monitoring system (DDMS) for driver drowsiness behavior recognition and analysis. First, an infrared camera is deployed in-vehicle to capture the driver’s facial and head information in naturalistic driving scenarios, in which the driver may or may not wear glasses or sunglasses. Second, we propose and design a multi-modal features representation approach based on facial landmarks, and head pose which is retrieved in a convolutional neural network (CNN) regression model. Finally, an extreme learning machine (ELM) model is proposed to fuse the facial landmark, recognition model and pose orientation for drowsiness detection. The DDMS gives promptly warning to the driver once a drowsiness event is detected.

The advancements in automation, big data computing and high bandwidth networking has expedited the realization of Industrial Internet of Things (IIoT). IIoT has made inroads into many sectors including automotive, semiconductors, electronics, etc. Particularly, it has created numerous opportunities in the automotive manufacturing sector to realize the new aura of platform concepts such as smart material flow control. This paper provides a thought provoking application of IIoT in automotive composites body shop. By creating a digital twin for every physical part, we no longer need to adhere to the conventional manufacturing processes and layouts, thus opening up new opportunities in terms of equipment and space utilization. The century-old philosophy of the assembly line might not be the best layout for vehicle manufacturing, thus proposing a novel assembly grid layout inspired from a colony of ants working to accomplish a common goal.

This paper presents a hierarchical control architecture to coordinate a group of connected vehicles on signalized intersection roads, where vehicles are allowed to change lane to follow a prescribed path. The proposed hierarchical control strategy consists of two control levels: a high level controller at the intersection and a decentralized low level controller in each car. In the hierarchical control architecture, the centralized intersection controller estimates the target velocity for each approaching connected vehicle to avoid red light stop based on the signal phase and timing (SPAT) information. Each connected vehicle as a decentralized controller utilizes model predictive control (MPC) to track the target velocity in a fuel efficient manner. The main objective in this paper is to consider mandatory lane changes. As in the realistic scenarios, vehicles are not required to drive in single lane. More specifically, they more likely change their lanes prior to signals.

The NASA-wide CEV Smart Buyer Team (SBT) was assembled in January 2006 and was tasked with the development of a NASA in-house design for the CEV Crew Module (CM), Service Module (SM), and Launch Abort System (LAS). This effort drew upon over 250 engineers from all of the 10 NASA Centers. In 6 weeks, this in-house design was developed. The Thermal Systems Team was responsible for the definition of the active and passive design architecture. The SBT effort for Thermal Systems can be best characterized as a design architecting activity. Proof-of-concepts were assessed through system-level trade studies and analyses using simplified modeling. This nimble design approach permitted definition of a point design and assessing its design robustness in a timely fashion. This paper will describe the architecting process and present trade studies and proposed thermal designs

Development of new air revitalization system (ARS) technology can initially be performed in a subscale laboratory environment, but in order to advance the maturity level, the technology must be tested in an end-to-end integrated environment. The Air Revitalization Technology Evaluation Facility (ARTEF) at the NASA Johnson Space Center (JSC) serves as a ground test bed for evaluating emerging ARS technologies in an environment representative of spacecraft atmospheres. At the center of the ARTEF is a hypobaric chamber which serves as a sealed atmospheric chamber for closed loop testing. A Human Metabolic Simulator (HMS) was custom-built to simulate the consumption of oxygen, and production of carbon dioxide, moisture and heat by up to eight persons. A variety of gas analyzers and dew point sensors are used to monitor the chamber atmosphere and the process flow upstream and downstream of a test article. A robust vacuum system is needed to simulate the vacuum of space.

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.

The importance of being able to determine the usage rate of life support subsystem consumables was recognized well before the first Apollo Extravehicular Activity (EVA). Since that time, metabolic activity levels have been evaluated and recorded for each EVA crew member. Throughout the history of the United States space program, EVA metabolic rates have been shown to be variable depending upon the mission scenario and the equipment used. Knowing this historic information is invaluable for current EVA planning activities, as well as for the design of future Extravehicular Mobility Unit (EMU) systems. This paper presents an overview of historic metabolic expenditures for Apollo, Skylab, and Shuttle missions, along with a discussion of the types of EVA crew member activities which lead to various metabolic rate levels, and a discussion on how this data is being used to develop advanced EMU systems.

NASA's Constellation Program, which includes the mission objectives of establishing a permanently-manned lunar Outpost, and the exploration of Mars, poses new and unique challenges for human life support systems that will require solutions beyond the Shuttle and International Space Station state of the art systems. In particular, the requirement to support crews for extended durations at the lunar outpost with limited resource resupply capability will require closed-loop regenerative life support systems with minimal expendables. Planetary environmental conditions such as lunar dust and extreme temperatures, as well as the capability to support frequent and extended-duration Extra-vehicular Activity's (EVA's) will be particularly challenging.

The International Space Station (ISS) program is nearing an assembly complete configuration with the addition of the final resource node module in early 2010. The Node 3 module will provide critical functionality in support of permanent long duration crews aboard ISS. The new module will permanently house the regenerative Environment Control and Life Support Systems (ECLSS) and will also provide important habitability functions such as waste management and exercise facilities. The ISS program has selected the Port side of the Node 1 “Unity” module as the permanent location for Node 3 which will necessitate architecture changes to provide the required interfaces. The USOS ECLSS fluid and ventilation systems, Internal Thermal Control Systems, and Avionics Systems require significant modifications in order to support Node 3 interfaces at the Node 1 Port location since it was not initially designed for that configuration.

Long duration human space missions, as planned in the Vision for Space Exploration, will not be possible without applying unprecedented levels of automation to support the human endeavors. The automated and robotic systems must carry the load of routine “housekeeping” for the new generation of explorers, as well as assist their exploration science and engineering work with new precision. Fortunately, the state of automated and robotic systems is sophisticated and sturdy enough to do this work — but the systems themselves have never been human-rated as all other NASA physical systems used in human space flight have. Our intent in this paper is to provide perspective on requirements and architecture for the interfaces and interactions between human beings and the astonishing array of automated systems; and the approach we believe necessary to create human-rated systems and implement them in the space program.

This paper presents a methodology for designing a simple open-loop steering robot profile to simulate a double lane change maneuver for track testing of a heavy tractor/trailer combination vehicle. For track testing of vehicles in a lane change type of maneuver, a human driver is typically used with a desired path defined with visual cues such as traffic cones. Such tests have been shown to result in poor test repeatability due to natural variation in driver steering behavior. While a steering robot may be used to overcome this repeatability issue, such a robot typically implements open-loop maneuvers and cannot be guaranteed to cause the vehicle to accurately follow a pre-determined trajectory. This paper presents a method using offline simulation to design an open-loop steering maneuver resulting in a realistic approximation of a double lane change maneuver.

Race teams compete at a level where fractions of a second separate the finishers. Consequently, teams devote significant resources to gain a competitive edge. Limitations on track time and high track rental prices dictate efficiency in testing. Thus, proper use of data acquisition and computer aided engineering tools is essential. These tools can be used to quickly analyze test data and serve as the basis for recommendations for changes in chassis setup and driver technique. This project describes the further development of such a tool that can be used to analyze and diagnose the control inputs of a driver as well as diagnose the overall balance of the chassis (i.e., understeer and oversteer). This tool is an “expert system” (implemented in MATLAB) that provides an understanding of the effects of both chassis setup changes and driver steering, braking, and throttle control inputs on overall lap times.

Over the last couple decades, there has been a growing interest in incorporating commercial off-the-shelf (COTS) technologies and open standards in the design of human-rated spacecraft. This approach is intended to reduce development and upgrade costs, lower the need for new design work, eliminate reliance on individual suppliers, and minimize schedule risk. However, it has not traditionally been possible for COTS solutions to meet the high reliability and fault tolerance requirements of systems implementing critical spacecraft functions. Byzantine faults are considered particularly dangerous to such systems because of their ability to escape traditional means of fault containment and disrupt consensus between system components. In this paper, we discuss the design of a voting protocol using Time-Triggered Ethernet capable of achieving data integrity in the presence of a single Byzantine fault.

Accurate in-cylinder air charge estimation is important for engine torque determination, controlling air-to-fuel ratio, and ensuring high after-treatment efficiency. Spark ignition (SI) engine technologies like variable valve timing (VVT) and exhaust gas recirculation (EGR) are applied to improve fuel economy and reduce pollutant emissions, but they increase the complexity of air charge estimation. Increased air-path complexity drives the need for cost effective solutions that produce high air mass prediction accuracy while minimizing sensor cost, computational effort, and calibration time. A large number of air charge estimation techniques have been developed using a range of sensors sets combined with empirical and/or physics-based models. This paper provides a technical review of research in this area, focused on SI engines.

The Advanced Integration Matrix (AIM) project at the Johnson Space Center (JSC) was chartered to study and solve systems-level integration issues for exploration missions. One of the first issues identified was an inability to conduct trade studies on control system architectures due to the absence of mature evaluation criteria. Such architectures are necessary to enable integration of regenerative life support systems. A team was formed to address issues concerning software and hardware architectures and system controls.. The team has investigated what is required to integrate controls for the types of non-linear dynamic systems encountered in advanced life support. To this end, a water processing bioreactor testbed is being developed which will enable prototyping and testing of integration strategies and technologies.

Long-duration missions in space will require regenerative air revitalization processes. Human testing of these regenerative processes is necessary to provide focus to the system development process and to provide realistic metabolic and hygiene inputs. To this end, the Lyndon B. Johnson Space Center (JSC), under the sponsorship of NASA Headquarters Office of Life and Microgravity Sciences and Applications, is implementing an Early Human Testing (EHT) Project. As part of this project, an integrated physicochemical Air Revitalization System (ARS) is being developed and tested in JSC's Life Support Systems Integration Facility (LSSIF). The components of the ARS include a Four-Bed Molecular Sieve (4BMS) Subsystem for carbon dioxide (CO2) removal, a Sabatier CO2 Reduction Subsystem (CRS), and a Solid Polymer Electrolyte (SPE)™ Oxygen Generation Subsystem (OGS). A Trace Contaminant Control Subsystem (TCCS) will be incorporated at a later date.

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.

A single radiator cooling system architecture has been widely applied in ground vehicles for safe equipment (e.g., engine block, electronics, and motors) temperature control. The introduction of multiple smaller heat exchangers provides additional energy management features and alternate pathways for continued operation in case of critical subsystem failure. Although cooling performance is often designed for maximum thermal loads, systems typically operate at a fraction of the peak values for most of their life cycle. In this project, a two-radiator configuration with variable flow rates and valve positions has been mathematically modelled and experimentally validated to study its performance feasibility. A multi-node resistance-capacitance thermal model was derived using the ε−NTU approach with accompanying convective and conductive heat transfer pathways within the system.

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.