Automotive Applications Of Hardware In The Loop Hil Simulation

Automotive Applications of Hardware-in-the-Loop (HIL) Simulation shines a light on HIL simulation testing methodology commonly used in the automotive industry for conventional, electrification and autonomy applications and can serve as an introductory resource for college students looking to join the automotive industry or experienced technical professionals who need a deeper understanding on what is HIL simulation, what are its benefits and how can it be used in their respective organizations.

Software-Hardware Integration in Automotive Product Development brings together a must-read set of technical papers on one the most talked-about subjects among industry experts The carefully selected content of this book demonstrates how leading companies, universities, and organizations have developed methodologies, tools, and technologies to integrate, verify, and validate hardware and software systems. The automotive industry is no different, with the future of its product development lying in the timely integration of these chiefly electronic and mechanical systems. The integration activities cross both product type and engineering discipline boundaries to include chip-, embedded board-, and network/vehicle-level systems. Integration, verification, and validation of each of these three domains are examined in depth, attesting to the difficulties of this phase of the automotive hardware and software system life cycle. The current state of the art is to integrate, verify, validate, and test automotive hardware and software with a complement of physical hardware and virtual software prototyping tools. The growth of sophisticated software tools, sometimes combined with hardware-in-the-loop devices, has allowed the automotive industry to meet shrinking time-to-market, decreasing costs, and increasing safety demands. It is also why most of the papers in this book focus on virtual systems, prototypes, and models to emulate and simulate both hardware and software. Further, such tools and techniques are the way that hardware and software systems can be “co-verified” and tested in a concurrent fashion. The goal of this compilation of expert articles is to reveal the similarities and differences between the integration, verification, and validation (IVV) of hardware and software at the chip, board, and network levels. This comparative study will reveal the common IVV thread among the different, but ultimately related, implementations of hardware and software systems. In so doing, it supports the larger systems engineering approach for the vertically integrated automobile—namely, that of model-driven development.

The book includes contributions on the latest model-based methods for the development of personal and commercial vehicle control devices. The main topics treated are: application of simulation and model design to development of driver assistance systems; physical and database model design for engines, motors, powertrain, undercarriage and the whole vehicle; new simulation tools, methods and optimization processes; applications of simulation in function and software development; function and software testing using HiL, MiL and SiL simulation; application of simulation and optimization in application of control devices; automation approaches at all stages of the development process.

For the last century, the automotive industry has been dominated by internal combustion engines. Their flexibility of application, driving range, performance and sporty characteristics has resulted in several generations of this technology and has formed generations of engineers. But that is not the end of the story. Stricter legislation and increased environmental awareness have resulted in the development of new powertrain technologies in addition and parallel to the highly optimized internal combustion engine. Hybrid powertrains systems, pure battery electric systems and fuel cell systems, in conjunction with a diverse range of applications, have increased the spectrum of powertrain technologies. Furthermore, automated driving together with intelligent and highly connected systems are changing the way to get from A to B. Not only is the interaction of all these new technologies challenging, but also several different disciplines have to collaborate intensively in order for new powertrain systems to be successfully developed. These new technologies and the resulting challenges lead to an increase in system complexity. Approaches such as systems engineering are necessary to manage this complexity. To show how systems engineering manages the increasing complexity of modern powertrain systems, by providing processes, methods, organizational aspects and tools, this book has been structured into five parts. Starting with Challenges for Powertrain Development, which describes automotive-related challenges at different levels of the system hierarchy and from different point of views. The book then continues with the core part, Systems Engineering, in which all the basics of systems engineering, model-based systems engineering, and their related processes, methods, tools, and organizational matters are described. A special focus is placed on important standards and the human factor. The third part, Automotive Powertrain Systems Engineering Approach, puts the fundamentals of systems engineering into practice by adding the automotive context. This part focuses on system development and also considers the interactions to hardware and software development. Several approaches and methods are presented based on systems engineering philosophy. Part four, Powertrain Development Case Studies, adds the practical point of view by providing a range of case studies on powertrain system level and on powertrain element level and discusses the development of hybrid powertrain, internal combustion engines, e-drives, transmissions, batteries and fuel cell systems. Two case studies on a vehicle level are also presented. The final part, Outlook, considers the development of systems engineering itself with particular focus on information communication technologies. Even though this book covers systems engineering from an automotive perspective, many of the challenges, fundamental principles, conclusions and outlooks can be applied to other domains too. Therefore, this book is not only relevant for automotive engineers and students, but also for specialists in scientific and industrial positions in other domains and anyone who has to cope with the challenge of successfully developing complex systems with a large number of collaborating disciplines.

Vehicle Power Management addresses the challenge of improving vehicle fuel economy and reducing emissions without sacrificing vehicle performance, reliability and durability. It opens with the definition, objectives, and current research issues of vehicle power management, before moving on to a detailed introduction to the modeling of vehicle devices and components involved in the vehicle power management system, which has been proven to be the most cost-effective and efficient method for initial-phase vehicle research and design. Specific vehicle power management algorithms and strategies, including the analytical approach, optimal control, intelligent system approaches and wavelet technology, are derived and analyzed for realistic applications. Vehicle Power Management also gives a detailed description of several key technologies in the design phases of hybrid electric vehicles containing battery management systems, component optimization, hardware-in-the-loop and software-in-the-loop. Vehicle Power Management provides graduate and upper level undergraduate students, engineers, and researchers in both academia and the automotive industry, with a clear understanding of the concepts, methodologies, and prospects of vehicle power management.

Technologies and Approaches to Reducing the Fuel Consumption of Medium- and Heavy-Duty Vehicles evaluates various technologies and methods that could improve the fuel economy of medium- and heavy-duty vehicles, such as tractor-trailers, transit buses, and work trucks. The book also recommends approaches that federal agencies could use to regulate these vehicles' fuel consumption. Currently there are no fuel consumption standards for such vehicles, which account for about 26 percent of the transportation fuel used in the U.S. The miles-per-gallon measure used to regulate the fuel economy of passenger cars. is not appropriate for medium- and heavy-duty vehicles, which are designed above all to carry loads efficiently. Instead, any regulation of medium- and heavy-duty vehicles should use a metric that reflects the efficiency with which a vehicle moves goods or passengers, such as gallons per ton-mile, a unit that reflects the amount of fuel a vehicle would use to carry a ton of goods one mile. This is called load-specific fuel consumption (LSFC). The book estimates the improvements that various technologies could achieve over the next decade in seven vehicle types. For example, using advanced diesel engines in tractor-trailers could lower their fuel consumption by up to 20 percent by 2020, and improved aerodynamics could yield an 11 percent reduction. Hybrid powertrains could lower the fuel consumption of vehicles that stop frequently, such as garbage trucks and transit buses, by as much 35 percent in the same time frame.

A comprehensive treatment of systems and software testing using state of the art methods and tools This book provides valuable insights into state of the art software testing methods and explains, with examples, the statistical and analytic methods used in this field. Numerous examples are used to provide understanding in applying these methods to real-world problems. Leading authorities in applied statistics, computer science, and software engineering present state-of-the-art methods addressing challenges faced by practitioners and researchers involved in system and software testing. Methods include: machine learning, Bayesian methods, graphical models, experimental design, generalized regression, and reliability modeling. Analytic Methods in Systems and Software Testing presents its comprehensive collection of methods in four parts: Part I: Testing Concepts and Methods; Part II: Statistical Models; Part III: Testing Infrastructures; and Part IV: Testing Applications. It seeks to maintain a focus on analytic methods, while at the same time offering a contextual landscape of modern engineering, in order to introduce related statistical and probabilistic models used in this domain. This makes the book an incredibly useful tool, offering interesting insights on challenges in the field for researchers and practitioners alike. Compiles cutting-edge methods and examples of analytical approaches to systems and software testing from leading authorities in applied statistics, computer science, and software engineering Combines methods and examples focused on the analytic aspects of systems and software testing Covers logistic regression, machine learning, Bayesian methods, graphical models, experimental design, generalized regression, and reliability models Written by leading researchers and practitioners in the field, from diverse backgrounds including research, business, government, and consulting Stimulates research at the theoretical and practical level Analytic Methods in Systems and Software Testing is an excellent advanced reference directed toward industrial and academic readers whose work in systems and software development approaches or surpasses existing frontiers of testing and validation procedures. It will also be valuable to post-graduate students in computer science and mathematics.