Written by two of the most respected, experienced and well-known researchers and developers in the field (e.g., Kiencke worked at Bosch where he helped develop anti-breaking system and engine control; Nielsen has lead joint research projects with Scania AB, Mecel AB, Saab Automobile AB, Volvo AB, Fiat GM Powertrain AB, and DaimlerChrysler. Reflecting the trend to optimization through integrative approaches for engine, driveline and vehicle control, this valuable book enables control engineers to understand engine and vehicle models necessary for controller design and also introduces mechanical engineers to vehicle-specific signal processing and automatic control. Emphasis on measurement, comparisons between performance and modelling, and realistic examples derive from the authors’ unique industrial experience . The second edition offers new or expanded topics such as diesel-engine modelling, diagnosis and anti-jerking control, and vehicle modelling and parameter estimation. With only a few exceptions, the approaches

This textbook introduces advanced control systems for vehicles, including advanced automotive concepts and the next generation of vehicles for ITS.

The introduction of mechatronic components for the powertrain, steering and braking systems opens the way to automatic driving functions. Together with internal and environmental sensors, various driver assistance systems are going to be developed for improving driving comfort and safety. Automatic driving control functions suppose a well-designed vehicle behavior. In order to develop and implement the software-based control functions mathematical vehicle models for the stationary and dynamic behavior are required. The book first introduces basic theoretically derived models for the tire traction and force transfer, the longitudinal, lateral, roll and pitch dynamic behavior and related components, like suspensions, steering systems and brakes. These models have to be tailored to allow an identification of the many unknown parameters during driving, also in dependence of different road conditions, velocity and vehicle load. Based on these mathematical models drive dynamic control systems are developed for semi-active and active suspensions, hydraulic and electromechanical brakes including ABS, traction and steering control. Then driver assistance systems like adaptive cruise control (ACC), electronic stability control (ESC), electronic course control and anti-collision control systems are considered. The anti-collision systems are designed and tested for emergency braking, emergency steering and avoiding of overtaking accidents. The book is dedicated to automotive engineers as well as to graduate students of mechanical, electrical and mechatronic engineering and computer science.

Automotive Air-conditioning and Climate Control Systems is a complete text and reference on the theoretical, practical and legislative aspects of vehicle climate control systems for automotive engineering students and service professionals. It provides the reader with a thorough up-to-date knowledge of current A/C systems, refrigerants and the new possible replacement systems like CO2, and includes unrivalled coverage of electronic and electrical control. Filling the gap in the automotive engineering and servicing market for students and those training on the job, this book will help both newcomers and those with more experience of air-conditioning systems maintenance engineering to keep up with the latest developments and legislation. - Detailed coverage of European and US vehicle HVAC systems - Thorough explanation of current and future systems including CO2 - Meets relevant C&G, IMI, and HND vocational and professional qualifications - IMI recommended reading material - Includes practical cases studies and examples from design and manufacturing companies including Ford, Vauxhall, Toyota, VW, Visteon, Sanden and others, accompanied by over 300 detailed illustrations and photographs

Vehicle Dynamics and Control provides a comprehensive coverage of vehicle control systems and the dynamic models used in the development of these control systems. The control system applications covered in the book include cruise control, adaptive cruise control, ABS, automated lane keeping, automated highway systems, yaw stability control, engine control, passive, active and semi-active suspensions, tire-road friction coefficient estimation, rollover prevention, and hybrid electric vehicles. In developing the dynamic model for each application, an effort is made to both keep the model simple enough for control system design but at the same time rich enough to capture the essential features of the dynamics. A special effort has been made to explain the several different tire models commonly used in literature and to interpret them physically. In the second edition of the book, chapters on roll dynamics, rollover prevention and hybrid electric vehicles have been added, and the chapter on electronic stability control has been enhanced. The use of feedback control systems on automobiles is growing rapidly. This book is intended to serve as a useful resource to researchers who work on the development of such control systems, both in the automotive industry and at universities. The book can also serve as a textbook for a graduate level course on Vehicle Dynamics and Control.

Control systems have come to play an important role in the performance of modern vehicles with regards to meeting goals on low emissions and low fuel consumption. To achieve these goals, modeling, simulation, and analysis have become standard tools for the development of control systems in the automotive industry. Modeling and Control of Engines and Drivelines provides an up-to-date treatment of the topic from a clear perspective of systems engineering and control systems, which are at the core of vehicle design. This book has three main goals. The first is to provide a thorough understanding of component models as building blocks. It has therefore been important to provide measurements from real processes, to explain the underlying physics, to describe the modeling considerations, and to validate the resulting models experimentally. Second, the authors show how the models are used in the current design of control and diagnosis systems. These system designs are never used in isolation, so the third goal is to provide a complete setting for system integration and evaluation, including complete vehicle models together with actual requirements and driving cycle analysis. Key features: Covers signals, systems, and control in modern vehicles Covers the basic dynamics of internal combustion engines and drivelines Provides a set of standard models and includes examples and case studies Covers turbo- and super-charging, and automotive dependability and diagnosis Accompanied by a web site hosting example models and problems and solutions Modeling and Control of Engines and Drivelines is a comprehensive reference for graduate students and the authors’ close collaboration with the automotive industry ensures that the knowledge and skills that practicing engineers need when analysing and developing new powertrain systems are also covered.

Automotive control has developed over the decades from an auxiliary te- nology to a key element without which the actual performances, emission, safety and consumption targets could not be met. Accordingly, automotive control has been increasing its authority and responsibility – at the price of complexity and di?cult tuning. The progressive evolution has been mainly ledby speci?capplicationsandshorttermtargets,withthe consequencethat automotive control is to a very large extent more heuristic than systematic. Product requirements are still increasing and new challenges are coming from potentially huge markets like India and China, and against this ba- ground there is wide consensus both in the industry and academia that the current state is not satisfactory. Model-based control could be an approach to improve performance while reducing development and tuning times and possibly costs. Model predictive control is a kind of model-based control design approach which has experienced a growing success since the middle of the 1980s for “slow” complex plants, in particular of the chemical and process industry. In the last decades, severaldevelopments haveallowedusing these methods also for “fast”systemsandthis hassupporteda growinginterestinitsusealsofor automotive applications, with several promising results reported. Still there is no consensus on whether model predictive control with its high requi- ments on model quality and on computational power is a sensible choice for automotive control.