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Erschienen in:
Prologue: Artificial Intelligence for Energy Transition Kapitel lesen Erstes Kapitel lesen

2020 | OriginalPaper | Buchkapitel

11. Using Model-Based Reasoning for Self-Adaptive Control of Smart Battery Systems

verfasst von : Franz Wotawa

Erschienen in: Artificial Intelligence Techniques for a Scalable Energy Transition

Verlag: Springer International Publishing

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Abstract

Keeping the power supply of autonomous and electrical vehicles working even in case of faults is of uttermost importance in order to maintain the desired behavior during operation. Especially in case of increased autonomy faults occurring in the power supply when driving should not require the vehicle to stop operation immediately. Instead the autonomous vehicle should still be able to reach a safe state like an emergency lane or a parking space. In this chapter, we introduce a method that enables the development of battery systems that react on internal or external faults in a smart way. In particular, we discuss model-based reasoning for this purpose and show its application for configuring and diagnosing systems. Besides discussing the foundations behind model-based reasoning, we make use of a smart battery system as a case study. In addition, we describe how to use the corresponding physical model for fault detection and a logical model for computing the root cause of the observed failure. The intention behind the chapter is to provide all necessary details of the methods allowing to adapt the methods to implement similar smart adaptive systems.

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Vorheriges Kapitel Neurofuzzy Approach for Control of Smart Appliances for Implementing Demand Response in Price Directed Electricity Utilization
Nächstes Kapitel Data-Driven Predictive Flexibility Modeling of Distributed Energy Resources
Fußnoten
1
The function ⌊⌋ rounds to the nearest smaller integer value.
 
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Metadaten
Titel
Using Model-Based Reasoning for Self-Adaptive Control of Smart Battery Systems
verfasst von
Franz Wotawa
Copyright-Jahr
2020
Buch
Artificial Intelligence Techniques for a Scalable Energy Transition

Print ISBN: 978-3-030-42725-2

Electronic ISBN: 978-3-030-42726-9

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-3-030-42726-9_11

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