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In the last years, lithium-ion batteries (LIBs) have become the most important energy storage system for consumer electronics, electric vehicles, and smart grids. A LIB is composed of several unit cells. Therefore, one of the most important factors that determine the performance of a LIB are the characteristics of the unit cell. The design of LIB cells is a challenging problem since it involves the evaluation of expensive black-box functions. These functions lack a closed-form expression and require long-running time simulations or expensive physical experiments for their evaluation. Recently, Bayesian optimization has emerged as a powerful gradient-free optimization methodology to solve optimization problems that involve the evaluation of expensive black-box functions. Bayesian optimization has two main components: a probabilistic surrogate model of the black-box function and an acquisition function that guides the optimization.

This paper presents experimental results that validate eco-driving and eco-heating strategies developed for connected and automated vehicles (CAVs). By exploiting vehicle-to-infrastructure (V2I) communications, traffic signal timing, and queue length estimations, optimized and smoothed speed profiles for the ego-vehicle are generated to reduce energy consumption. Next, the planned eco-trajectories are incorporated into a real-time predictive optimization framework that coordinates the cabin thermal load (in cold weather) with the speed preview, i.e., eco-heating. To enable eco-heating, the engine coolant (as the only heat source for cabin heating) and the cabin air are leveraged as two thermal energy storages. Our eco-heating strategy stores thermal energy in the engine coolant and cabin air while the vehicle is driving at high speeds, and releases the stored energy slowly during the vehicle stops for cabin heating without forcing the engine to idle to provide the heating source.

Electrical connectors and terminals are widely used in the automotive industry. It is desirable to mate the electrical connections using materials or coatings with low friction force to improve the ergonomics of the assembly process while maintaining good electrical conduction over the lifetime of the vehicle. We have previously shown that plasma-enhanced chemical vapor deposition (PECVD) of graphene on gold (Au) and silver (Ag) terminals can significantly reduce the insertion force (friction force during the terminal insertion process). However, the cost of this deposition method is rather high, and its high temperature process (> 400 oC) makes it impractical for materials with low melting temperatures. For example, tin (Sn) coating with a melting temperature of 232 oC is commonly used in electrical connectors, which cannot sustain the high temperature process. In this study, reduced graphene oxide was prepared using a low-cost solution process and applied onto metallic terminals.

The design of better active materials for lithium-ion batteries (LIBs) is crucial to satisfy the increasing demand of high performance batteries for portable electronics and electric vehicles. Currently, the development of new active materials is driven by physical experimentation and the designer’s intuition and expertise. During the development process, the designer interprets the experimental data to decide the next composition of the active material to be tested. After several trial-and-error iterations of data analysis and testing, promising active materials are discovered but after long development times (months or even years) and the evaluation of a large number of experiments. Bayesian global optimization (BGO) is an appealing alternative for the design of active materials for LIBs. BGO is a gradient-free optimization methodology to solve design problems that involve expensive black-box functions. An example of a black-box function is the prediction of the cycle life of LIBs.

Inside an automobile, hundreds of connectors and electrical terminals in various locations experience different corrosive environments. These connectors and electrical terminals need to be corrosion-proof and provide a good electrical contact for a vehicle’s lifetime. Saltwater and sulfuric acid are some of the main corrosion concerns for these electrical terminals. Currently, various thin metallic layers such as gold (Au), silver (Ag), or tin (Sn) are plated with a nickel (Ni) layer on copper alloy (Cu) terminals to ensure reliable electrical conduction during service. Graphene due to its excellent chemical stability can serve as a corrosion protective layer and prevent electrochemical oxidation of metallic terminals. In this work, effects of thin graphene layers grown by plasma-enhanced chemical vapor deposition (PECVD) on Au and Ag terminals and thin-film devices were investigated. Various mechanical, thermal/humidity, and electrical tests were performed.

Green Light Optimized Speed Advisory (GLOSA) systems have the objective of providing a recommended speed to arrive at a traffic signal during the green phase of the cycle. GLOSA has been shown to decrease travel time, fuel consumption, and carbon emissions; simultaneously, it has been demonstrated to increase driver and passenger comfort. Few studies have been conducted using historical cycle-by-cycle phase probabilities to assess the performance of a speed advisory capable of recommending a speed for various traffic signal operating modes (fixed-time, semi-actuated, and fully-actuated). In this study, a GLOSA system based on phase probability is proposed. The probability is calculated prior to each trip from a previous week’s, same time-of-day (TOD) and day-of-week (DOW) period, traffic signal controller high-resolution event data.

The transportation sector is facing three revolutions: shared mobility, electrification, and autonomous driving. To inform decision making and guide smart transportation system development at the city-level, it is critical to model and evaluate how travelers will behave in these systems. Two key components in such models are (1) individual travel demands with high spatial and temporal resolutions, and (2) travelers’ sociodemographic information and trip purposes. These components impact one’s acceptance of autonomous vehicles, adoption of electric vehicles, and participation in shared mobility. Existing methods of travel demand generation either lack travelers’ demographics and trip purposes, or only generate trips at a zonal level. Higher resolution demand and sociodemographic data can enable analysis of trips’ shareability for car sharing and ride pooling and evaluation of electric vehicles’ charging needs.

In order to improve efficiency and increase the operation of electric vehicles, assistive energy regeneration systems can be used. A hydraulic energy recovery system is modeled to be used as a regenerative system for supplementing energy storage for a pure electric articulated passenger bus. In this study a pump/motor machine is modeled to transform kinetic energy into hydraulic energy during braking, to move the hydraulic fluid from the low pressure reservoir to the hydraulic accumulator. The simulation of the proposed system was used to estimate battery savings. It was found that on average, approximately 39% of the battery charge can be saved when using a real bus driving cycle.

Typically, earthmoving machines do not have wheel suspensions. This lack of components often causes uncomfortable driving, and in some cases reduces machine productivity and safety. Several solutions to this problem have been proposed in the last decades, and particularly successful is the passive solution based on the introduction of accumulators in the hydraulic circuit connecting the machine boom. The extra capacitance effect created by the accumulator causes a magnification of the boom oscillations, in such a way that these oscillations counter-react the machine oscillation caused by the driving on uneven ground. This principle of counter-reacting machine oscillations through the boom motion can be achieved also with electro-hydraulic solutions, properly actuating the flow supply to the boom actuators on the basis of a feedback sensors and a proper control strategy.

The vertical force generated from terrain-tire interaction has long been of interest for vehicle dynamic simulations and chassis development. To improve simulation efficiency while still providing reliable load prediction, a terrain pre-filtering technique using a constraint mode tire model is developed. The wheel is assumed to convey one quarter of the vehicle load constantly. At each location along the tire's path, the wheel center height is adjusted until the spindle load reaches the pre-designated load. The resultant vertical trajectory of the wheel center can be used as an equivalent terrain profile input to a simplified tire model. During iterative simulations, the filtered terrain profile, coupled with a simple point follower tire model is used to predict the spindle force. The same vehicle dynamic simulation system coupled with constraint mode tire model is built to generate reference forces.

A novel Blended Hydraulic Hybrid transmission architecture is presented in this paper with benefits over conventional designs. This novel configuration combines elements of a hydrostatic transmission, a parallel hybrid, and a selectively connectable high pressure accumulator using passive and actively controlled logic elements. Losses are reduced compared to existing series hybrid transmissions by enabling the units to operate efficiently at pressures below the current high pressure accumulator's pressure. A selective connection to the high pressure accumulator also allows for higher system precharge which increases regenerative braking torque and energy capture with little determent to system efficiency. Finally operating as a hydrostatic transmission increases transmission stiffness (i.e. driver response) and may improve driver feel in certain situations when compared to a conventional series hybrid transmission.

A parallel-through-the-road (PTTR) plug-in hybrid electric vehicle is being created by modifying a 2013 Chevrolet Malibu. This is being accomplished by replacing the stock 2.4L gasoline engine which powers the front wheels of the vehicle with a 1.7L diesel engine and by placing a high voltage electric motor in the rear of the vehicle to power the rear wheels. In order to meet the high voltage needs of the vehicle created by the PTTR hybrid architecture, an energy storage system (ESS) will need to be created. This paper explains considerations, such as location, structure integrity, and cooling, which are needed in order to properly design an ESS.

The Purdue University EcoMakers team has completed its first year of the EcoCAR 2 Competition, in which the team has designed a Parallel-Through-the-Road Plug-in Hybrid Electric Vehicle that meets the performance requirements of a mid-size sedan for the US market, maintaining capability, utility and consumer satisfaction while minimizing emissions, energy consumption and petroleum use. The team is utilizing a 1.7L 14 CI engine utilizing B20 (20% biodiesel, 80% diesel), a 16.2 kW-hr A123 battery pack, and a Magna E-Drive motor to power the front and rear wheels. This will allow the vehicle to have a charge-depleting range of 75 miles. The first year was focused on the simulation of the vehicle, in which the team completed the controls, packaging and integration, and electrical plans for the vehicle to be used and implemented in years two and three of the competition.

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 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.

Conventional suspension analysis of three-dimensional suspensions typically use two-dimensional analyses. This is done by projecting suspension components onto two-dimensional planes and then performing a two-dimensional analysis in each of these orthogonal planes or neglecting motions in one of the planes entirely. This requires multiple iterations because changes in one plane require a checking of their effects on motion in the other orthogonal planes. In doing so, much of the insight and accuracy gained from a three-dimensional analysis can be lost. A three-dimensional kinematic analysis approach is presented and applied to a dual A-Arm suspension system. All motions are considered instantaneously about a screw axis instead of a point as used by the usual two-dimensional modeling approach. The model predicts deflections of suspension components in response to the three-dimensional forces present at the contact patch.

Electric machinery is typically based upon the interaction of magnetic fields and current to produce electromagnetic force or torque. However, force and torque can also be produced through the use of electric fields. The purpose of this investigation is to briefly analyze the use of a switched capacitance electric field based machine to see if it may have aerospace applications for use as either propulsion motor for unmanned aerospace vehicle (UAV) or lightweight flywheel applications for aerospace applications. It is shown that although its use as a hub propulsion motor is not feasible, it may be a candidate for use in a power flywheel energy storage system.

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.

“Truck Ride” in this study refers to some vehicle ride parameters involved in tractor-trailer combinations. For the study, a mathematical model of a tractor-trailer vehicle as a vibrating system was developed. Principles of vibration theory were applied to the model while a digital computer was employed to investigate the complex system. To parallel the analytical investigation of the tractor-trailer vehicle, vehicle studies were conducted using a magnetic tape recorder and associated instrumentation installed in the tractor. Parameters studied included coupler position on the tractor, laden weight of trailer, spring rates of the different axles of the combination, damping capacity associated with each spring rate, vehicle speed, and “tar strip” spacing of the highway and cab mountings. The mathematical results were used as a basis for empirical study. A comparison of calculated and empirical data are reported.