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A multiple-injection combustion strategy has been developed for heated gasoline direct injection compression ignition (HGCI). Gasoline was injected into a 0.4L single cylinder engine at a fuel pressure of 300bar. Fuel temperature was increased from 25degC to a temperature of 280degC by means of electric injector heater. This approach has the potential of improving fuel efficiency, reducing harmful CO and UHC as well as particulate emissions, and reducing pressure rise rates. Moreover, the approach has the potential of reducing fuel system cost compared to high pressure (>500bar) gasoline direct injection fuel systems available in the market for GDI SI engines that are used to reduce particulate matter. In this study, a multiple injection strategy was developed using electric heating of the fuel prior to direct fuel injection at engine speed of 1500rpm and load of 12.3bar IMEP.

Today’s advanced vehicles have high degree of interaction due to numerous sensors, actuators and also with complex communication within the control units. In order to hack a vehicle, it has to be within a certain range of communication. Here, we discuss the On-Board Diagnostic (OBD) regulations for next generation BEV/HEV, its vulnerabilities and cybersecurity threats that come with hacking. We propose three cybersecurity attack detection and defense methods: Cyber-Attack detection algorithm, Time-Based CAN Intrusion Detection Method and, Feistel Cipher Block Method. These control methods autonomously diagnose a cybersecurity problem in a vehicle’s onboard system using an OBD interface, such as OBD-II when a fault caused by a cyberattack is detected, All of this is achieved in an internal communication network structure. The results discussed here focus on the first detection method that is Cyber-Attack detection algorithm.

Designing a vehicle for superior crash safety performance in consumer rating tests such as US-NCAP is a compelling target in the design of passenger vehicles. In today’s context, there is also a high emphasis on making a vehicle as lightweight as possible which calls for an efficient design. In modern vehicle design, these objectives can only be achieved through Computer-Aided Engineering (CAE) for which a detailed CAD (Computer-Aided Design) model of a vehicle is a pre-requisite. In the absence of the latter (i.e. a matured CAD model) at the initial and perhaps the most crucial phase of vehicle body design, a rational approach to design would be to resort to a knowledge-based methodology which can enable crash safety assessment of an assumed design using artificial intelligence techniques such as neural networks.

Vehicle weight-driven design comes amid rising higher fuel efficiency standards and must meet the criteria—pass proving ground (PG) test events that are equivalent to customer usage. Computer-aided engineering (CAE) fatigue analysis for PG is a successful push behind to digitally simulate vehicle durability performance with high fidelity. The need for vehicle weight reduction often arises in the vehicle development final phases when CAE methods, time, and tangible cost-effective opportunities are limited or nonexistent. In this research, a new CAE methodology is developed to identify opportunities for lightweight hole placement in the chassis structure and deliver a cost-effective lightweight solution with no additional impact on fatigue life. The successful application of this new methodology exhibits the effectiveness of the truck frame, which is the key chassis structure to support the body, suspension, and powertrain.

Previous study suggested that female, thin, obese, and older occupants had a higher risk of death and serious injury in motor vehicle crashes. Human body finite element models were a valuable tool in the study of injury biomechanics. The mesh deformation method based on radial basis function(RBF) was an attractive alternative for morphing baseline model to target models. Generally, when a complex model contained many elements and nodes, it was impossible to use all surface nodes as landmarks in RBF interpolation process, due to its prohibitive computational cost. To improve the efficiency, the current technique was to averagely select a set of nodes as landmarks from all surface nodes. In fact, the location and the number of selected landmarks had an important effect on the accuracy of mesh deformation. Hence, how to select important nodes as landmarks was a significant issue. In the paper, an efficient peak point-selection RBF mesh deformation method was used to select landmarks.

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

There has been a keen interest in recent times on implementation of lightweight materials in vehicles to bring down the unladen weight of a vehicle for enhancing fuel efficiency. Fiber-reinforced composites comprise a class of such materials. As sustainability is also a preoccupation of current product development engineers including vehicle designers, bio-composites based on natural fibers are receiving a special attention. Keeping these motivations of lower effective density, environment friendliness and occupational safety in mind, woven jute fabric based composites have been recently studied as potential alternatives to glass fiber composites for structural applications in automobiles. In the past, mechanical characterization of jute-polyester composites were restricted to obtaining their stress-strain behaviors under quasi-static conditions.

The ‘boundary of space’ model representing all possible positions which may be occupied by a mechanism during its normal range of motion (for all positions and orientations) is called the work envelope. In the robotic domain, it is also known as the robot operating envelope or workspace. Several researchers have investigated workspace boundaries for different degrees of freedom (DOF), joint types and kinematic structures utilizing many approaches. The work envelope provides essential boundary information, which is critical for safety and layout concerns, but the work envelope information does not by itself determine the reach feasibility of a desired configuration. The effect of orientation is not captured as well as the coupling related to operational parameters. Included in this are spatial occupancy concerns due to linking multiple kinematic chains, which is an issue with multi-tasking machine tools, and manufacturing cells.

When performing trajectory planning for robotic applications, there are many aspects to consider, such as the reach conditions, joint and end-effector velocities, accelerations and jerk conditions, etc. The reach conditions are dependent on the end-effector orientations and the robot kinematic structure. The reach condition feasibility is the first consideration to be addressed prior to optimizing a solution. The ‘functional’ work space or work window represents a region of feasible reach conditions, and is a sub-set of the work envelope. It is not intuitive to define. Consequently, 2D solution approaches are proposed. The 3D travel paths are decomposed to a 2D representation via radial projections. Forward kinematic representations are employed to define a 2D boundary curve for each desired end effector orientation.

A collaborative robot or cobot is a robot that can safely and effectively interact with human workers while performing industrial tasks. The ability to work alongside humans has increased the importance of collaborative robots in the automation industry, as this unique feature is a much needed property among robots nowadays. Rethink Robotics has pioneered this unique discipline by building many robots including the Baxter Robot which is exclusive not only because it has collaborative properties, but because it has two arms working together, each with 7 Degrees Of Freedom. The main goal of this research is to validate the kinematic equations for the Baxter collaborative robot and develop a unified reconfigurable kinematic model for the Left and Right arms so that the calculations can be simplified.

Rigid polyurethane (PU) foam finds wide applications as a lightweight material in impact safety design such as improving occupant safety in vehicle crashes. The two principal reacting compounds for formulating such foam are variants of polyol and isocyanate. In the present study, an alternative mechanical engineering-based approach for determining, with confidence, the desirable ratio of reacting compounds for formulation of a rigid/crushable PU foam for mechanical applications is demonstrated. According to the present approach, PU foam samples are prepared by varying the mixing ratio over a wide range. The desirable mixing ratio is shown to be the one that optimizes key mechanical properties under compression such as total absorbed energy, specific absorbed energy and energy absorption efficiency.

Path planning and re-planning for serial 6 degree of freedom (DOF) robotic systems is challenging due to complex kinematic structure and application conditions which affects the robot's tool frame position, orientation and singularity avoidance. These three characteristics represent the key elements for production planning and layout design of the automated manufacturing systems. The robot trajectory represents series of connected points in 3D space. Each point is defined with its position and orientation related to the robot's base frames or predefined user frame. The robot will move from point to point using the desired motion type (linear, arc, or joint). The trajectory planning requires first to check if robot can reach the selected part(s). This can be simply done by placing the part(s) inside the robot's work envelope. The robot's work envelope represents a set of all robots' reachable points without considering their orientation.

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 investigating powertrain optimizations as a part of their participation in the EcoCAR2 design competition for the conversion of a 2013 Chevrolet Malibu into a plug-in hybrid. EcoCAR2 is the current three-year Department of Energy (DoE) Advanced Vehicle Technical Competition (AVTC) for 15 select university student teams competing on designing, building, and then optimizing their Plug-In Hybrid conversions of GM donated vehicles. WSU's powertrain design provides for approximately 56-64 km (35-40 miles) of electric driving before the Internal Combustion Engine (ICE) powertrain is needed. When the ICE is started, the ICE traditionally goes through a cold start with the engine, transmission, and final drive all at ambient temperature. The ICE powertrain components are most efficient when warmed up to their normal operating temperature, typically around 90-100 °C.

Low cetane JP-8 fuels have been identified as being difficult to use under conventional diesel operation. However, recent focus on low-temperature combustion (LTC) modes has led to an interest in distillate hydrocarbon fuels having high volatility and low autoignition tendency. An experimental study is performed to evaluate low-temperature combustion processes in a small-bore optically-accessible diesel engine operated in a partially-premixed combustion mode using low-cetane Sasol JP-8 fuel. This particular fuel has a cetane number of 25. Both single and dual injection strategies are tested. Since long ignition delay is a consequence of strong autoignition resistance, under the conditions examined, low cetane Sasol JP-8 combustion can only take place with a double injection strategy: one pilot injection event in the vicinity of exhaust TDC and one main injection event near firing TDC.

Wayne State University EcoCAR2 team is designing and modifying a GM-donated Chevrolet Malibu 2013 to a Parallel-Through-The-Road (PTTR) plug-in hybrid. A Freescale-donated Center Stack Unit (CSU) touchscreen display is used for Human Machine Interface (HMI). Surveys were conducted to better understand CSU functionality expectations. One required function was increasing driving efficiency. Other hybrid and electric vehicles HMI systems present driving and environmental settings efficiencies such as average fuel economy, lifetime fuel economy, electric charge used, fuel used, distances driven on each power source, instantaneous power gauge and instantaneous driver efficiency gauge. These offer drivers a large sum of information but with no provision to analyze and improve one's driving habits unless one has the required knowledge to understand the causes behind the values presented.

Shell Elements based Parametric Frame Modeling is a powerful CAE tool, which can generate robust frame design concept optimized for NVH and durability quickly when combined with Taguchi Design of Experiments. The scalability of this modeling method includes cross members length/location/section/shape, frame rail segments length/section and kick in/out/up/down angle, and access hole location & size. In the example of the D. O. E. study, more than fifteen parameters were identified and analyzed for frequency and weight. The upper and lower bounds were set for each design parameter based on package and manufacturing constraints. Sixteen Finite Element frame were generated by parametrically updating the base model, which shows this modeling method is comparatively convenient. Sensitivity of these sixteen parameters to the frequency and weight was summarized through statics, so the favorable design alternative can be achieved with the major parameters' combination.

Biodiesel has been widely accepted as an alternative for fossil-derived diesel fuel for use in compression ignition (CI) engines. Poor oxidative stability and cold flow properties restrict the use of biodiesel beyond current B20 blend levels (20% biodiesel in 80% ULSD) for vehicle applications. Maintaining the properties of B20 as specified by ASTM D7476-08 is important because, once out of spec, B20 may cause injector coke formation, fuel filter plugging, increased exhaust emissions, and overall loss of engine performance. While the properties of fresh B20 may be within the specifications, under engine operating and longer storage conditions B20 could deteriorate. In a diesel engine, the fuel that goes to the injector and does not enter the cylinder is recycled back to the fuel tank. The re-circulated fuel returns to the fuel tank at an elevate temperature, which can cause thermal oxidation.

Biomechanical surrogates are used in various forms to study head impact response in automotive applications and for assessing helmet performance. Surrogate headforms include those from the National Operating Committee on Standards for Athletic Equipment (NOCSAE) and the many variants of the Hybrid III. However, the response of these surrogates to loading at the chin and how that response may affect the loads transferred from the jaw to the rest of the head are unknown. To address part of that question, the current study compares the chin impact response performance of select human surrogates to that of the cadaver. A selection of Hybrid III and NOCSAE based surrogates with fixed and articulating jaws were tested under drop mass impact conditions that were used to describe post mortem human subject (PMHS) response to impacts at the chin (Craig et al., 2008). Results were compared to the PMHS response with cumulative variance technique (Rhule et al., 2002).

Lean Six Sigma is an approach that is gaining momentum both in manufacturing and service industries. Design for Lean Six Sigma (DFLSS) is an outgrowth of the DFSS and Lean Six Sigma approaches. The essence of DFLSS is to ensure design quality and predictability during the early design phases and the approach employs a structured integrated product development methodology and a comprehensive set of robust tools to drive product quality, innovation, faster time to market, and lower product costs. When it comes to automotive Product Development, applying lean principles and DFSS together becomes more of a challenge within the existing PD system. While the benefits of DFLSS present an attractive proposition in a fiercely competitive market it brings its own challenges as to how to deploy it for maximum benefits. This paper examines the challenges, potential and opportunities for DFLSS in the automotive industry and presents a vision for integrating it in to the Product Development System.