Automotive Science Mathematics

Despite the assistance provided by electronic control systems, the latest generation of passenger car chassis still relies heavily on conventional chassis elements. This book examines these conventional elements and their interactions with mechatronic systems within the context of driving dynamics. Chassis fundamentals and design are described in the initial chapters, followed by a practical examination of driving dynamics and detailed descriptions and explanations of modern chassis components. A separate section is devoted to axles and the processes used during axle development. This first English edition features a number of improvements over the latest German edition, including revised illustrations and several updates in the text and list of references.

This book highlights the mechanics of the elastic elements made of steel alloys with focus on the metal springs for automotive industry. The industry and scientific organizations study intensively the foundations of design of spring elements and permanently improve the mechanical properties of spring materials.

From Novice to Pro: FEA Proficiency Unleashed

Deep dive into EV Engineering to understand the science behind it

Providing a wide variety of technologies for ensuring the safety and dependability of cyber-physical systems (CPS), this book offers a comprehensive introduction to the architecture-centric modeling, analysis, and verification of CPS. In particular, it focuses on model driven engineering methods including architecture description languages, virtual prototyping, and formal analysis methods.

This volume presents a selection of case studies that address a substantial range of optimized object packings (OOP) and their applications. The contributing authors are well-recognized researchers and practitioners. The mathematical modelling and numerical solution aspects of each application case study are presented in sufficient detail. A broad range of OOP problems are discussed: these include various specific and non-standard container loading and object packing problems, as well as the stowing of hazardous and other materials on container ships, data centre resource management, automotive engineering design, space station logistic support, cutting and packing problems with placement constraints, the optimal design of LED street lighting, robust sensor deployment strategies, spatial scheduling problems, and graph coloring models and metaheuristics for packing applications. Novel points of view related to model development and to computational nonlinear, global, mixed integer optimization and heuristic strategies are also discussed.

Combine the power of Machine Learning, Deep Learning and Computer Vision to make a Self-Driving Car!

Combine the power of Machine Learning, Deep Learning and Computer Vision to make a Self-Driving Car!