![Practical Battery Design and Control](/uploads/posts/2023-05/1683932531_6301_practical_batt_ry_d_sign_and_control.jpg)
Автор: Naoki Matsumura
Издательство: Artech House
Год: 2023
Страниц: 301
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB
Covering what real-world battery engineers need to know, this book pulls together in one resource the many calculations and practical considerations that a battery engineer faces daily. It gives you the basics, including battery chemistry, design, impedance, charging, and manufacturing, as well as alternative energy solutions like supercapacitors, energy harvesting, and fuel cells. The book goes on to provide a detailed view of the field’s newest frontiers, such as Si anode, Li metal anode, and new Artificial Intelligence (AI), Machine Learning, and Deep Learning possibilities, and equips you with the practical knowledge with intuitive explanations you need to solve real-world battery problems and challenges. This is a great resource for battery engineers and managers looking to expand their knowledge to broader areas and better collaborate with other experts; new battery engineers who would like to learn the solutions to the potential real problems related to their day-to-day job; software and system designers who need essential and practical battery knowledge to use a battery or collaborate on a project.
Artificial Intelligence (AI), which includes Machine Learning (ML) and Deep Learning (DL), has been used everywhere in our lives, for example, internet search engine, image search, Natural Language Processing (NLP) including translation and autocomplete, and social media. The AI application has also been extended to battery algorithms, such as charging and fuel gauging. Algorithm development may be thought of as an area of software engineers. However, if battery engineers who already have battery knowledge also learn AI/ML/DL overview, creative collaboration with the software engineers is possible. For example, the battery engineer proposes an ML algorithm to extend battery longevity with chemistry knowledge and the software engineer optimizes the program with coding skill sets. This chapter explains basic knowledge of AI/ML/DL for battery engineers and how to use it with real examples.
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