Optimal and predictive power management for hybrid vehicles. Application for predefined itinerary plug-in city bus

Doctoral Thesis / Dissertation from the year 2012 in the subject Engineering - Automotive Engineering, grade: 2012, Beijing Institute of Technology (Department of Mechanical and Vehicular Engineering), course: predefined itinerary plug-in city bus"e;, language: English, abstract: In an era defined by environmental consciousness and the relentless pursuit of sustainable energy solutions, the optimization of hybrid and plug-in hybrid electric vehicles (HEVs and P-HEVs) stands as a critical frontier. This book delves into the intricate world of hybrid vehicle technology, offering a comprehensive exploration of modeling, simulation, and advanced power management strategies designed to maximize fuel efficiency and extend battery lifespan. Uncover the secrets behind cutting-edge techniques, including the application of dynamic programming and the innovative use of the Lagrange formalism, as we navigate the complexities of powertrain design and energy distribution. Explore the development of sophisticated, forward-looking models within the MATLAB/Simulink environment, meticulously crafted to emulate real-world driving conditions and provide invaluable insights into vehicle performance. Journey through a detailed comparative analysis of rule-based and optimal power management strategies for HEVs, unveiling the potential for significant fuel economy improvements through refined control algorithms. Discover how to optimize HEV fuel economy over the entire battery lifetime, balancing performance with longevity by carefully managing battery aging mechanisms and state-of-charge thresholds. Further, the book introduces a groundbreaking predictive power management strategy tailored for P-HEVs operating on predefined itineraries, such as city buses, leveraging real-time data and optimized Lagrange multipliers to achieve unparalleled energy efficiency and harness the full potential of regenerative braking. This book is an invaluable resource for automotive engineers, researchers, and anyone seeking a deeper understanding of the technologies driving the future of sustainable transportation, offering a pathway to a greener, more efficient automotive landscape. From exploring the nuances of hybrid vehicle topologies to the practical application of experimental validation using real-time test benches and dSPACE environments, this exploration offers a holistic view of HEV and P-HEV optimization, setting a new standard for innovation in the field and addressing pressing concerns related to fuel depletion, air pollution, global warming, and public health. It's time to unlock the full potential of hybrid technology and pave the way for a cleaner, more sustainable future of transportation.