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SAE 2011 High Efficiency IC Engines Symposium - Session 3 - Advanced Diesel Engine Technologies Presenter Andrew Brown, Delphi Corp.

Vehicle electrification is shaping the future of automotive mobility in terms of automotive power and propulsion. The market for New Energy Vehicles (HEV/PHEV/REEV/EV) as well as clean vehicle technologies is expected to grow steadily driven by government regulations mandating increased fuel economy and lower emissions. The fastest growth in this market will be in Asia Pacific, most notably China. The Chinese government has made its intentions clear on how important it considers the development and consumer purchase of hybrid and electric vehicles. The mandate is that by year 2012, vehicle manufacturers produce at least 500,000 units (or 5%) per year of their total output as hybrid and/or electric. All Chinese vehicle manufacturers must have at least one HEV or EV model in the market by the same year. Thus far China has invested over US$3.5 billion to stimulate the production of NEVs and the necessary infrastructure to support them.

A complete system approach to power semiconductor analysis and selection is set forth in this paper. In order to address design overkill, a suitable power profile across the desired drive schedule is obtained through vehicle simulation in lieu of worse case operating conditions. The representative profile is then applied to detailed models of the inverter, power device, and power device thermal stack-up in order to predict worse case, silicon junction temperature rise. The simulation stream includes a closed silicon thermal loop that leads to more accurate power loss and junction temperature calculations. The models are combined and exercised in a single platform for ease of integration and fast simulation. Herein, the methods will be applied to a working example of an inverter for motor drives, and analytical results will be reviewed.

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.

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 Department of Defense (DOD) has adopted the use of JP-8 under the “single battlefield fuel” policy. Fuel properties of JP-8 which are different from ULSD include cetane number, density, heating value and compressibility (Bulk modulus). While JP8 has advantages compared to ULSD, related to storage, combustion and lower soot emissions, its use cause a drop in the peak power in some military diesel engines. The engines that has loss in power use the Hydraulically actuated Electronic Unit Injection (HEUI) fuel system. The paper explains in details the operation of HEUI including fuel delivery into the injector and its compression to the high injection pressure before its delivery in the combustion chamber. The effect of fuel compressibility on the volume of the fuel that is injected into the combustion chamber is explained in details.

Accident statistics have shown that older and obese occupants are less adaptable to existing vehicle occupant restraint systems than ordinary middle-aged male occupants, and tend to have higher injury risk in vehicle crashes. However, the current research on injury mechanism of aging and obese occupants in vehicle frontal impacts is scarce. This paper focuses on the optimization design method of occupant restraint system parameters for specific body type characteristics. Three parameters, namely the force limit value of the force limiter in the seat belt, pretensioner preload of the seat belt and the proportionality coefficient of mass flow rate of the inflator were used for optimization. The objective was to minimize the injury risk probability subjected to constraints of occupant injury indicator values for various body regions as specified in US-NCAP frontal impact tests requirements.

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.

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.

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.

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.

The explosion of big data has created challenges for both cloud-based systems and Autonomous Vehicles (AVs) in data collection and management. The same challenges are now being realized in developing databases for integrated sensors, streaming, real-time and on-demand services in AVs. With just one AV expecting to generate over 30 Terabytes of data a day, modern NoSQL databases provide opportunities to horizontally scale AV data seamlessly. NoSQL provides solutions designed to accommodate a wide variety of data models such as, key-value, document, column and graph databases. Key-value stores are by nature scalable, fast processing, and distribute horizontally. These databases are tasked with handling several data types including IoT, radar, lidar, ultra-sonic sensors, GPS, odometry, and sensor data while providing streaming and real-time services. NoSQL can store and utilize structured, semi-structured, and unstructured data necessary for multimedia storage needs.

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.

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.

The piston secondary motion is an important phenomenon in internal combustion (IC) engine. It occurs due to the piston transverse and rotational motion during piston reciprocating motion. The piston secondary motion results in engine friction and engine noise. There has been lot of research activities going on in piston secondary motion using both analytical models and experimental studies. These studies are aimed at reducing the engine friction as well as the noise generated due to piston secondary motion. The aim of this paper is to compile the research actives carried out on the piston secondary motion and discuss the possible research opportunities for reducing the IC engine piston secondary motion.

This paper is an overview of the current state (calendar year 2010) of in-vehicle multiplexing and what pertinent technologies are emerging. Usage and trends of in-vehicle networking protocols will be presented and categorized. The past few years have seen a large growth in the number and type of communication buses used in automobiles, trucks, construction equipment, and military, among others. Development continues even into boating and recreation vehicles. Areas for discussion will include SAE Class A, B, C, Diagnostics, SafetyBus, Mobile Media, Wireless, and X-by-Wire. All existing mainstream vehicular multiplex protocols (approximately 40) are categorized using the SAE convention as well as categories previously proposed by this author. Top contenders will be pointed out along with a discussion of the protocol in the best position to become the industry standard in each category.

Estimation of vehicle roll angle, lateral velocity and side slip angle for the purpose of crash sensing is considered. Only roll rate sensor and the sensors readily available in vehicles equipped with ESC (Electronic Stability Control) systems are used in the estimation process. The algorithms are based on kinematic relationships, thus avoiding dependence on vehicle and tire models, which minimizes tuning efforts and sensitivity to parameter variations. The estimate of roll angle is obtained by blending two preliminary estimates, each valid in different conditions, in such a manner that the final estimate continuously favors the more accurate one. The roll angle estimate is used to compensate the gravity component in measured lateral acceleration due to vehicle roll or road bank angle. This facilitates estimation of lateral velocity and side slip angle from fundamental kinematic relationships involving the gravity-compensated lateral acceleration, yaw rate and longitudinal velocity.

In today's dynamic automotive environment, reducing the lead-time to introduce new product technologies to the market place can be a key competitive advantage. Employing proactive risk reduction techniques to define key product and process relationships is essential to enhance the production worthiness of a design while it is still in the advanced development phase of the program. This paper describes how Delphi Powertrain Systems applied the Shainin proactive risk reduction methodology in advanced product development to focus resources on understanding and mitigating the risk associated with the development of a new Delphi ammonia sensor. Organizational and technical strategies to accelerate profound knowledge capture, along with corresponding test results, are presented and discussed.

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.

In order to survive and thrive in harsh economic environments and capitalize on opportunities driven by the current regional and global needs for Safe, Green, and Connected solutions, companies are required to constantly create/innovate new products while shortening their time to market. These new requirements cannot be met with the traditional closed innovation approach. A new approach calls for working with “others” in order to benefit from complementary resources. Open Innovation is a means to empower collaborative innovation aimed at meeting the new requirements for fast paced, cost effective and yet innovative technology. This paper presents the key elements of Open Innovation from its birth to its implementation. Firstly, it describes Henry Chesbrough's OI model. Secondly, it suggests that a successful implementation of an OI model can be achieved though the application of Everett Rogers' theory of Diffusion of Innovations.