Abstract
The selection of the battery system has a significant impact on the state of electric vehicle (EV) technology. To access a battery's functional utilization, its capacity and the method utilized to determine its operating time is to be known. Based on load requirements, cell voltage, current, temperature readings, as well as anticipated battery state of charge, capacity, and impedance, battery monitoring system decides how efficiently to charge and discharge batteries. In this paper, a battery monitoring system is proposed to continuously track performance in comparison to the estimated battery capacity. This study suggests using the Raspberry Pi-Pico, a processor that can explore computation and access programming through interfaces, to implement a battery monitoring system. It can be combined with the framework for monitoring data, which can manage, watch, and log the data into an online database and send to user that can be monitored through the display (or android app).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Mathew SA, Prakash R, John PC (2012) A smart wireless battery monitoring system for electric vehicles. In: 12th international conference on intelligent systems design and applications (ISDA). Kochi, India, pp 189–193
Pareek S, Sujil A, Ratra S, Kumar R (2020) Electric vehicle charging station challenges and opportunities: a future perspective. In: 2020 international conference on emerging trends in communication, control and computing (ICONC3). Lakshmangarh, India, pp 1–6
Singirikonda S, Obulesu YP (2020) Battery modelling and state of charge estimation methods for energy management in electric vehicle-a review. In: IOP conference series, Material science Engineering, vol 937
Zhang C, Li K, Mcloone S, Yang Z (2014) Battery modelling methods for electric vehicles-a review. In: 2014 European control conference (ECC). pp 2673–2678
Liu W, Placke T, Chau KT (2022) Overview of batteries and battery management for electric vehicles. Energy Rep (8), 4058–4084
Ramkumar MS, Subba Rami Reddy C, Ramakrishnan A, Raja K, Pushpa S, Jose S, Jayakumar M (2022) Review on Li-Ion battery with battery management system in electrical vehicle. Adv Mater Sci Eng (2022):1–8
Vaideeswaran V, Bhuvanesh S, Devasena M (2019) Battery management systems for electric vehicles using lithium ion batteries. In: 2019 innovations in power and advanced computing technologies (i-PACT). Vellore, India, pp 1−9
Le Gall G, Montavont N, Papadopoulos GZ (2022) IoT network management within the electric vehicle battery management system. J Sign Process Syst 94:27–44
Mishra S, Swain SC, Samantaray RK (2021) A review on battery management system and its application in electric vehicle. In: 2021 international conference on advances in computing and communications (ICACC). Kochi, Kakkanad, India, pp 1–6
Senthilkumar M, Suresh KP, Sekar TG, Pazhanimuthu C (2021) Efficient battery monitoring system for E-Vehicles. In: 2021 7th international conference on advanced computing and communication systems (ICACCS). Coimbatore, India, pp 833–836
Kivrak S, Özer T, Oğuz Y (2018) Battery management system implementation with pasive control method. In: 2018 IV international conference on information technologies in engineering education (Inforino). Moscow, Russia, pp 1–4
Krishnakumar S et al (2022) IoT-based battery management system for E-Vehicles. In: 2022 3rd international conference on smart electronics and communication (ICOSEC). Trichy, India, pp 428–434
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Sobha Rani, P., Jyothi, B., Nagoor, S.K., Meghanadh, S. (2024). Battery Monitoring System for Electric Vehicles. In: Kumar, S., Tripathy, M., Jena, P. (eds) Control Applications in Modern Power Systems. EPREC 2023. Lecture Notes in Electrical Engineering, vol 1128. Springer, Singapore. https://doi.org/10.1007/978-981-99-9054-2_21
Download citation
DOI: https://doi.org/10.1007/978-981-99-9054-2_21
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-99-9053-5
Online ISBN: 978-981-99-9054-2
eBook Packages: EnergyEnergy (R0)