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Over the last decade, a number of hybrid architectures have been proposed with the main goal of minimizing energy consumption of off-highway vehicles. One of the architecture subsets which has progressively gained attention is hydraulic hybrids for earth-moving equipment. Among these architectures, hydraulic hybrids with secondary-controlled drives have proven to be a reliable, implementable, and highly efficient alternative with the potential for up to 50% engine downsizing when applied to excavator truck-loading cycles. Multi-input multi-output (MIMO) robust linear control strategies have been developed by the authors' group with notable improvements on the control of the state of charge of the high pressure accumulator. Nonetheless, the challenge remains to improve the actuator position and velocity tracking.

The Chevrolet Volt is an electric vehicle with extended-range that is capable of operation on battery power alone, and on engine power after depletion of the battery charge. First generation Chevrolet Volts were driven over half a billion miles in North America from October 2013 through September 2014, 74% of which were all-electric [1, 12]. For 2016, GM has developed the second-generation of the Volt vehicle and “Voltec” propulsion system. By significantly re-engineering the traction power inverter module (TPIM) for the second-generation Chevrolet Volt extended-range electric vehicle (EREV), we were able to meet all performance targets while maintaining extremely high reliability and environmental robustness. The power switch was re-designed to achieve efficiency targets and meet thermal challenges. A novel cooling approach enables high power density while maintaining a very high overall conversion efficiency.

Development pace of new embedded projects often requires usage of model-based design process (MBD). More individuals start using MBD without previous experience with tools and new processes. Matlab/Simulink/Stateflow is a common tool that is used in control applications in automotive and airspace industries. Because of its complexity, the tool has a steep learning curve. Therefore, it is vitally important to set the MBD environment that allows persons to develop real-life projects even without a deep knowledge of the tool. The quality of the product should not be compromised and the development time should not be extended due to the initial lack of knowledge of the tool by the developers. The shifting to MBD leads to changes of roles and responsibilities of algorithm designers and software implementers. This shift is due to ability of creating of efficient production code by code generators.

Conventional hydraulic steering systems keep improving performance and driving comfort by introducing advanced features via mechanical design. The ever increasing mechanical complexity requires the advanced modeling and simulation technology to mitigate the risks in the early stage of the development process. In this paper, we focus on advanced modeling tools environment with an example of a load sensing hydraulic steering system. The complete system architecture is presented. Analytical equations are developed for a priority valve and a steering control unit as the foundation of modeling. The full version of hydraulic steering system model is developed in Dymola platform. In order to capture interaction between steering and vehicle, the co-simulation platform between the hydraulic steering system and vehicle dynamics is established by integrating Dymola, Carsim and Simulink.

Excessive vibration and poor controllability occur in many mobile fluid power applications, with negative consequences as concerns operators' health and comfort as well as machine safety and productivity. This paper addresses the problem of reducing oscillations in fluid power machines presenting a novel control technique of general applicability. Strong nonlinearities of hydraulic systems and the unpredictable operating conditions of the specific application (e.g. uneven ground, varying loads, etc.) are the main challenges to the development of satisfactory general vibration damping methods. The state of the art methods are typically designed as a function of the specific application, and in many cases they introduce energy dissipation and/or system slowdown. This paper contributes to this research by introducing an energy efficient active damping method based on feedback signals from pressure sensors mounted on the flow control valve block.

A temperature estimation algorithm (thermal observer) that provides accurate estimates of the thermal states of an electric machine in real time is presented. The thermal observer is designed to be a Kalman filter that combines thermal state predictions from a lumped-parameter thermal model of the electric machine with temperature measurements from a single external temperature sensor. An analysis based on the error covariance matrix of the Kalman filter is presented to guide the selection of the best sensor location. The thermal observer performance is demonstrated using a 3.8 kW permanent-magnet machine. Comparison of the thermal observer estimates and the actual temperatures demonstrate that this approach can provide accurate knowledge of the machine's thermal states despite modeling uncertainty and unknown initial machine thermal states.

The new devices and missions to achieve the aims of NASA's Science Mission Directorate (SMD) are creating increasingly demanding thermal environments and applications. In particular, the low conductance of metal-to-metal interfaces used in the thermal switches lengthen the cool-down phase and resource usage for spacecraft instruments. During this work, we developed and tested a vacuum-compatible, durable, heat-conduction interface that employs carbon nanotube (CNT) arrays directly anchored on the mating metal surfaces via microwave plasma-enhanced, chemical vapor deposition (PECVD). We demonstrated that CNT-based thermal interface materials have the potential to exceed the performance of currently available options for thermal switches and other applications.

There has always been, from the very first UAV, a need for providing cost-effective methods of deploying unmanned aircraft systems at high altitudes. Missions for UAVs at high altitudes are used to conduct atmospheric research, perform global mapping missions, collect remote sensing data, and establish long range communications networks. The team of Gevers Aircraft, Technology Management Group, and Purdue University have designed an innovative balloon launched UAV for these near space applications. A UAV (Payload Return Vehicle) with a nested morphing wing was designed in order to meet the challenges of high altitude flight, and long range and endurance without the need for descent rate control with rockets or a feathering mode.

Detailed computer models of system components for More Electric Aircraft have been developed using the Advanced Control System Language (ACSL) and its graphical front-end, Graphic Modeller. Among the devices modeled are a wound-rotor synchronous generator with parallel bridge-rectifier outputs, a switched-reluctance generator, and various loads including a DC-DC converter, an inverter-driven induction motor, and an electro-hydrostatic actuator. Results from the simulations are presented together with corroborating experimental test results.

Audio playbacks are mechanisms which read data from a storage medium and produce commands and signals which an audio system turns into music. Playbacks are constantly changed to meet market demands, requiring that the control software be updated quickly and efficiently. This paper reviews a 12 month project using the MATLAB/Simulink/Stateflow environment for model-based development, system simulation, autocode generation, and hardware-in-the-loop (HIL) verification for playbacks which read music CDs or MP3 disks. Our team began with a “clean slate” approach to playback architecture, and demonstrated working units running production-ready code. This modular, layered architecture enables rapid development and verification of new playback mechanisms, thereby reducing the time needed to evaluate playback mechanisms and integrate into a complete infotainment system.

As the speed and memory capabilities of microprocessors have increased, it has become more popular for the signal conditioning of knock sensor outputs to be performed entirely within the microprocessor. One method of this signal conditioning process utilizes the Discrete Fourier Transform (DFT). It is common for systems that use this method to limit the knock detection window to one length across all RPM and load points to reduce computation and memory constraints on the processor. This paper will summarize this method and explain a further enhancement, variable window length, that may become more popular as processor capabilities increase.

Early experience with precision farming technology suggests that some hardware and software may follow a rapid S curve adoption path, but that the use of integrated precision farming systems may take longer to develop and be subject to false starts and periods of stagnation. Yield monitors appear to be following a classic S curve adoption path. Precision farming adoption is like that of hybrid corn because changes in organizations will be required to use it effectively. It is like motorized mechanization because it is coming on the market in an immature form and lends itself to farmer tinkering.

Automotive radar application is a focus in active traffic safety research activities. And accurate lateral position estimation from the leading target vehicle through radar is of great interest. This paper presents a method based on the regression tree, which estimates the rear centroid of leading target vehicle with a long range FLR (Forward Looking Radar) of limited resolution with multiple radar detections distributed on the target vehicle. Hours of radar log data together with reference value of leading vehicle's lateral offset are utilized both as training data and test data as well. A ten-fold cross validation is applied to evaluate the performance of the generated regression trees together with fused decision forest for each percentage of the training data.

The negative consequences of unsafe behaviors on the job heavily contribute to the rising costs of doing business in terms of both organization dollars and diminished human quality of life. Developing a safety culture provides a positive proactive approach toward creating a working environment where safety is a top priority. An integral part of accomplishing this task is directly related to training individuals on how the interactions that occur among organizational members and the messages their behaviors send influence others' behaviors. This can be best addressed through communication skill development initiatives including mutual responsibility, trust, avoiding punitive strategies and facilitating assertiveness.

The need for greater capacity in automotive transportation (in the midst of constrained resources) and the convergence of key technologies from multiple domains may eventually produce the emergence of a “swarm” concept of operations. The swarm, a collection of vehicles traveling at high speeds and in close proximity, will require management techniques to ensure safe, efficient, and reliable vehicle interactions. We propose a shared-autonomy approach in which the strengths of both human drivers and machines are employed in concert for this management. A fuzzy logic-based control implementation is combined with a genetic algorithm to select the shared-autonomy architecture and sensor capabilities that optimize swarm operations.

Operation & support costs for military weapon systems accounted for approximately 3/5th of the $500B Department of Defense budget in 2006. In an effort to ensure readiness and decrease these costs for ground vehicle fleets, health monitoring technologies are being developed for Condition-Based Maintenance of individual vehicles within a fleet. Dynamics-based health monitoring is used in this work because vibrations are a passive source of response data, which are global functions of the mechanical loading and properties of the vehicle. A common way of detecting faults in mechanical equipment, such as the suspension and chassis of a ground vehicle, is to compare measured operational vibrations to a reference (or healthy) signature to detect anomalies.

The FCC allocated the 5.9 GHz spectrum to enhance the safety and productivity of the nations transportation system. Dedicated Short Range Communication (DSRC) is a medium range wireless communication protocol that supports vehicle-to-vehicle, vehicle-to-roadside, and roadside-to-vehicle communication. It enables both public safety and licensed private transactions. DSRC contrasts cellular and Wi-Fi by providing fast acquisition, low latency communication in a relatively close communication range. IEEE is developing the Wireless Access in Vehicular Environment (WAVE) communication standards to provide the groundwork for DSRC and enable seamless, interoperable services. The WAVE architecture includes IEEE P1609.1 (Application layer), IEEE P1609.2 (Security layer), IEEE P1609.3 (Network layer), IEEE P1609.4 (Upper MAC Layer), and IEEE 802.11p (Lower MAC and Physical layers).

Vehicle Infrastructure Integration (VII) is an initiative of the US Department of Transportation to provide communications among vehicles and between vehicles and roadside infrastructure in order to increase the safety and productivity of transportation systems. It makes use of but is not restricted to the 5.9 GHz Dedicated Short Range Communication (DSRC) spectrum. There are 3 major categories of applications for VII - Highway Safety, Vehicular Mobility, and Consumer & Commercial Services. There are currently approximately 42,000 traffic fatalities a year in the United States. Reducing deaths, injuries and property damage is of the highest priority in the development of VII applications. Electronic Brake Warning, Signal Phase and Timing, and Collision Detection are among the applications dedicated to improving highway safety. Increasing traffic volume is outpacing the addition of new roadway capacity, resulting in increasing delays, congestion and frustration.

This paper introduces an integration-level analysis tool to provide feedback for high-level trade spaces. The Purdue University Lunar C3I Model integrates approximations of several domain-specific models to simulate for many years the effect of network and asset parameters. This paper discusses the communication, anomaly response, and autonomy simulation models in depth. Results of these models provide specific examples of integration-level figures of merit that can be useful for comparing different campaign implementations. These figures of merit are contrasted with related domain-specific figures of merit in order to demonstrate the need for higher-level system integration decisions. A final example of integration-level results and interpretation discusses the autonomy level of the Altair lunar lander.

A low-cost hydrostatic absorption dynamometer has been developed for small to medium sized engines. The dynamometer was designed and built by students to support student projects and educational activities. The availability of such a dynamometer permits engine break-in cycles, performance testing, and laboratory instruction in the areas of engines, fuels, sensors, and data acquisition. The dynamometer, capable of loading engines up to 60kW at 155Nm and 3600rpm, incorporates a two-section gear pump and an electronically operated proportional pressure control valve to develop and control the load. A bypass valve permits the use of only one pump section, allowing increased fidelity of load control at lower torque levels. Torque is measured directly on the drive shaft with a strain gage. Torque and speed signals are transmitted by an inductively-powered collar mounted to the dynamometer drive shaft. Pressure transducers at the pump inlet and pump outlet allow secondary load measurement.