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In this paper, we proposed a distributed Engineering Computer Aided Learning System. Instead of attending engineering teaching sessions, engineering students are able to interact with the software to gain the same amount of teaching materials. Besides, they will interact with other engineering students from other Engineering schools. The proposed software has the ability to examine the student step by step to reach certain goals. The training and the examination will be different based on the student level and his learning process. Using this system the role of excellent professor can be achieved. The software will have two sessions, i.e. test session and learning session. The software provides the capability of knowledge sharing between multi schools and different educational systems that can provide the students with a large set of training materials. The system was built using JAVA programming language.

Contemporary manufacturing systems are still evolving. The system elements, layouts, and integration methods are changing continuously, and ‘collaborative robots’ (CoBots) are now being considered as practical industrial solutions. CoBots, unlike traditional CoBots, are safe and flexible enough to work with humans. Although CoBots have the potential to become standard in production systems, there is no strong foundation for systems design and development. The focus of this research is to provide a foundation and four tier framework to facilitate the design, development and integration of CoBots. The framework consists of the system level, work-cell level, machine level, and worker level. Sixty-five percent of traditional robots are installed in the automobile industry and it takes 200 hours to program (and reprogram) them.

The adoption of lithium-ion batteries in vehicle electrification is fast growing due to high power and energy demand on hybrid and electric vehicles. However, the battery overall performance changes with time through the vehicle life. This paper investigates the electric vehicle battery cell aging under different usages. Battery cell experimental data including open circuit voltage and internal resistance is utilized to build a typical electric vehicle model in the AVL-Cruise platform. Four driving cycles (WLTP, UDDS, HWFET, and US06) with different ambient temperatures are simulated to acquire the battery cell terminal currents. These battery cell terminal current data are inputs to the MATLAB/Simulink battery aging model. Simulation results show that battery degrades quickly in high ambient temperatures. After 15,000 hours usage in 50 degrees Celsius ambient temperature, the usable cell capacity is reduced up to 25%.

Speed and accuracy are the critical needs in software for the modeling and simulation of vehicle cooling systems. Currently, there are two approaches used in commercially available thermal analysis software packages: 1) detailed modeling using complex and sophisticated three-dimensional (3D) heat transfer and computational fluid dynamics, and 2) rough modeling using one-dimensional (1D) simplistic network solvers (flow and thermal) for quick prediction of flow and thermal fields. The first approach offers accuracy at the cost of speed, while the second approach provides the simulation speed, sacrificing accuracy and can possibly lead to oversimplification. Therefore, the analyst is often forced to make a choice between the two approaches, or find a way to link or couple the two methods. The linking between one-dimensional and three-dimensional models using separate software packages has been attempted and successfully accomplished for a number of years.

In this paper, we present a project being conducted at Yalong Educational Equipment Company on control of educational robots using discrete event system theory. An educational robot is a programmable robot to be used by students for training and learning. To model a robot, we divide the robot into nine physical modules. Each module is modeled as an automaton. Parallel composition is used to obtain the entire model. The robot can be programmed to perform sequences of basic tasks. We investigate six basic tasks and use supervisors to control and achieve the tasks. Desired languages are obtained for all tasks and supervisory control theory is used to synthesize supervisors. To reduce computational complexity, modular/coordinated supervisors are used

This paper details the control system development process for the University of Washington (UW) EcoCAR 2 team over the three years of the competition. Particular emphasis is placed upon the control system development and validation process executed during Year 3 of the competition in an effort to meet Vehicle Technical Specifications (VTS) established and refined by the team. The EcoCAR 2 competition challenges 15 universities across North America to reduce the environmental impact of a 2013 Chevrolet Malibu without compromising consumer acceptability. The project takes place over a three year design cycle, where teams select a hybrid architecture and fuel choice before defining a set of VTS goals for the vehicle. These VTS are selected based on the desired static and dynamic performance targets to balance fuel consumption and emissions with consumer acceptability requirements.

It is well known that thermal management is a key factor in design and performance analysis of Lithium-ion (Li-ion) battery, which is widely adopted for hybrid and electric vehicles. In this paper, an air cooled battery thermal management system design has been proposed and analyzed for mild hybrid vehicle application. Computational Fluid Dynamics (CFD) analysis was performed using CD-adapco's STAR-CCM+ solver and Battery Simulation Module (BMS) application to predict the temperature distribution within a module comprised of twelve 40Ah Superior Lithium Polymer Battery (SLPB) cells connected in series. The cells are cooled by air through aluminum cooling plate sandwiched in-between every pair of cells. The cooling plate has extended the cooling surface area exposed to cooling air flow. Cell level electrical and thermal simulation results were validated against experimental measurements.

The Wayne State University EcoCAR2 team provided its members with Modeling and Simulation training course for the second summer of the competition. EcoCAR2 is a three-year Advanced Vehicle Technology Competition (AVTC) sponsored by General Motors and the Department of Energy. The course lasted three months and included 45 hours of formal lectures and class hands-on work and an estimated one hundred and fifty hours in home assignments that directly contributed to the team's deliverables. The course described here is unique. The design and class examples were extracted from an in-house complete vehicle simulation and control code to ensure hands-on, interactive training based on real-world problems. The course investigated the physics behind every major powertrain component of a hybrid electric vehicle and the different ways to model the components into a full vehicle simulation.

Up to now, there is no standard methodology that addresses how driver distraction is affected by perceptual demand and working memory demand - aside from visual allocation. In 2009, the Peripheral Detection Task (PDT) became a NHTSA recommended measure for driver distraction [1]. Then the PDT task was renamed as the Detection Response Task (DRT) because the International Standards Organization (ISO) has identified this task as a potential method for assessing selective attention in detection of visual, auditory, tactile and haptic events while driving. The DRT is also under consideration for adoption as an ISO standard surrogate test for driver performance for new telematics designs. The Wayne State University (WSU) driver imaging group [2, 3] improved the PDT and created the Enhanced Peripheral Detection Task I (EPDT-I) [4]. The EPDT-I is composed of a simple visual event detection task and a video of a real-world driving scene.

EcoCAR 2: Plugging in to the Future (EcoCAR) is North America's premier collegiate automotive engineering competition, challenging students with systems-level advanced powertrain design and integration. The three-year Advanced Vehicle Technology Competition (AVTC) series is organized by Argonne National Laboratory, headline sponsored by the U. S. Department of Energy (DOE) and General Motors (GM), and sponsored by more than 30 industry and government leaders. Fifteen university teams from across North America are challenged to reduce the environmental impact of a 2013 Chevrolet Malibu by redesigning the vehicle powertrain without compromising performance, safety, or consumer acceptability. During the three-year program, EcoCAR teams follow a real-world Vehicle Development Process (VDP) modeled after GM's own VDP. The EcoCAR 2 VDP serves as a roadmap for the engineering process of designing, building and refining advanced technology vehicles.

The effect of many operating parameters on the instantaneous frictional (IFT) torque was determined experimentally in a single cylinder diesel engine. The method used was the (P - ω)method developed earlier at Wayne State University. The operating parameters were load, lubricating oil grade, oil, temperature and engine speed. Also IFT was determined under simulated motoring conditions, commonly used in engine friction measurements. The results showed that the motoring frictional torque does not represent that under firing conditions even under no load. The error reached 31.4% at full load. The integrated frictional torque over the whole cycle and the average frictional torque were determined. A comparison of the average frictional torque under load was compared with the average motoring torque.

Hybrid electric vehicle (HEV) is one of the most highly pursued technologies for improving energy efficiency while reducing harmful emissions. Thermal modeling and control play an ever increasing role with HEV design and development for achieving the objective of improving efficiency, and as a result of additional thermal loading from electric powertrain components such as electric motor, motor controller and battery pack. Furthermore, the inherent dual powertrains require the design and analysis of not only the optimal operating temperatures but also control and energy management strategies to optimize the dynamic interactions among various components. This paper presents a complete development process and simulation results for an efficient modeling approach with integrated control strategy for the thermal management of plug-in HEV in parallel-through-the road (PTTR) architecture using a flexible-fuel engine running E85 and a battery pack as the energy storage system (ESS).

The Wayne State University (WSU) EcoCAR2 student team is participating in a design competition for the conversion of a 2013 Chevrolet Malibu into a plug-in hybrid. The team created a repeatable on-road test drive route using local public roads near the university that would be of similar velocity ranges contained in the EcoCAR2 4-Cycle Drive Schedule - a weighted combination of four different EPA-based drive cycles (US06 split into city and highway portions, all of the HWFET, first 505 seconds portion of UDDS). The primary purpose of the team's local on-road route was to be suitable for testing the team's added hybrid components and control strategy for minimizing petroleum consumption and tail pipe emissions. Comparison analysis of velocities was performed between seven local routes and the EcoCAR2 4-Cycle Drive Schedule. Three of the seven local routes had acceptable equivalence for velocity (R₂ ≻ 0.80) and the team selected one of them to be the on-road test drive route.

A series of 10 full-scale experimental simulations of pedestrian-vehicle impact was carried out using cadavers and a 95th percentile anthropomorphic dummy. The test subjects were impacted laterally and frontally at 24, 32 and 40 km/h (15, 20 and 24 mph). Each subject was extensively instrumented with miniature accelerometers, up to a maximum of 53 transducers. The nine-accelerometer scheme was used to measure angular acceleration of body segments from which it was possible to compute the head injury criterion (HIC) for cadaver head impact. A full-size Chevrolet was used as the impacting vehicle. The impact event was three-dimensional in nature during which the body segments executed complex motions. Dummy impacts were more repeatable than cadaver impacts but the response of these test subjects were quite different. The HIC was higher for head-hood impact than for head-ground impact in two of the cases analyzed.

A new inter-disciplinary degree program has been developed at Lawrence Technological University: the Master of Science in Mechatronic Systems Engineering Degree (MS/MSE). It is one of a few MS-programs in mechatronics in the U.S.A. today. This inter-disciplinary program reflects the main areas of ground vehicle mechatronic systems and robotics. This paper presents areas of scientific and technological principles which the Mechanical Engineering, Electrical and Computer Engineering, and Math and Computer Science Departments bring to Mechatronic Systems Engineering and the new degree program. New foundations that make the basis for the program are discussed. One of the biggest challenges was developing foundations for mechanical engineering in mechatronic systems design and teaching them to engineers who have different professional backgrounds. The authors first developed new approaches and principles to designing mechanical subsystems as components of mechatronic systems.

The purpose of the Institute for Manufacturing Research (IMR) is to enhance Wayne State University's existing technological strength in the areas of manufacturing research which have demonstrated potential benefits for the State's economy. IMR's faculty conduct basic and applied research in selected areas of manufacturing science. The research programs within the Institute are broadly interdisciplinary and industrially interactive, and are organized around the following areas: materials development, modification, and nondestructive evaluation; software technology for manufacturing and engineering; and product reliability and machine tool research. Faculty from eight departments within the Colleges of Science and Engineering participate in IMR.

As vehicles are getting electrified and more intelligent, the energy consumption of the auxiliary system increases rapidly. The auxiliary battery acts as the backbone of the system to support the proper operation of the vehicle. It is important to ensure the auxiliary battery has enough energy to meet the basic loads regardless the vehicle is in park or running. However, the existing methods only focus on auxiliary energy management when the vehicle is in a dynamic event. To fulfill the gap, we propose an intelligent strategy that detects the low state of charge (SOC) condition, temporarily turns down the auxiliary loads based on their priorities and charges the auxiliary battery at the maximum efficiency of the auxiliary power unit. In addition, the proposed strategy allows the vehicle to get the park duration update and make intelligent decisions on charging the auxiliary battery.

The kinematics of rear-end collisions based on published acceleration pulses of actual car-to-car collisions (10 and 23 mph) were reproduced on a crash simulator using anthropomorphic dummies, human cadavers, and a volunteer. Comparison of the responses of subjects without head support were based on the reactions developed at the base of the skull (occipital condyles). The cadavers gave responses which were representative of persons unaware of an impending collision. The responses of both dummies used were not comparable with those of the cadavers or volunteer, or to each other. An index based on voluntary human tolerance limits to statically applied head loads was developed and used to determine the severity of the simulations for the unsupported head cases. Results indicated that head torque rather than neck shear or axial forces is the major factor in producing neck injury.

An iterative learning control (ILC) algorithm has been developed for a test cell electro-hydraulic, fully flexible valve actuation system to track valve lift profile under steady-state and transient operation. A dynamic model of the plant was obtained from experimental data to design and verify the ILC algorithm. The ILC is implemented in a prototype controller. The learned control input for two different lift profiles can be used for engine transient tests. Simulation and bench test are conducted to verify the effectiveness and robustness of this approach. The simple structure of the ILC in implementation and low cost in computation are other crucial factors to recommend the ILC. It does not totally depend on the system model during the design procedure. Therefore, it has relatively higher robustness to perturbation and modeling errors than other control methods for repetitive tasks.

Lithium-ion polymer battery has been widely used for vehicle onboard electric energy storage ranging from 12V SLI (Starting, Lighting, and Ignition), 48V mild hybrid electric, to 300V battery electric vehicle. Formulation on cell parameters acquired from minimum numbers of experiments, the modeling and simulation could be an effective approach in predicting battery performance, thermal effectiveness, and degradation. This paper describes the modeling, simulation, and validation of Lithium-Nickel-Manganese-Cobalt-Oxide (LiNiMnCoO2) based cell with 3.6V nominal voltage and 20Ah capacity. Constant current 20A, 40A, 60A, and 80A discharge tests are conducted in the computer-controlled cycler and temperature chamber. Discharging voltage curves and cell surface temperature distributions are recorded in each discharging test. A three-dimensional cell model is constructed in the COMSOL multi-physics platform based on the cell parameters.