April 15, 2024

Architectures, opportunities and challenges of the battery internet for electric vehicles

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BEV technology system architecture based on systems engineering. Credit: Green energy and smart transportation

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BEV technology system architecture based on systems engineering. Credit: Green energy and smart transportation

An article describing the architectures, opportunities and challenges of the Internet of Batteries (IoB) was published in the magazine. Green energy and smart transportation.

Current battery technology used in electric vehicles (EV) faces several critical challenges. Firstly, the limited operating range of electric vehicles remains a major concern for potential users, as it affects their ability to travel long distances without the need for frequent recharging.

Additionally, long charging times are inconvenient for users and may hinder the widespread adoption of electric vehicles. In addition to these limitations, the possibility of battery failure, such as thermal runaway, can create safety risks, including fire or explosion. These factors could deter potential users from adopting electric vehicles, including technical concerns about battery health and safety, the need for frequent recharging, and long charging times.

Additionally, electric vehicle batteries experience degradation over time, which decreases performance and reduces battery life. It leads to increased maintenance and risk of accidents for electric vehicle owners.

As a promising solution to these problems, IoB is a networked system that uses Internet of Things (IoT) principles to collect data from electric vehicle batteries. This data is then transmitted to a cloud server, where it is used to estimate battery health, perform predictive analytics, and diagnose faults. Unlike traditional battery management systems (BMS), IoB leverages advanced technologies such as IoT, cloud computing and machine learning to provide intelligent battery management.


How machine learning works within the IoB system. Credit: Green energy and smart transportation

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How machine learning works within the IoB system. Credit: Green energy and smart transportation

The IoB can be defined as an integrated system that uses IoT and cloud computing technology to monitor and manage batteries. IoB systems can collect real-time battery data such as voltage, current, temperature, and other parameters. This data can be used to analyze battery health and performance, identify potential failures, and optimize battery usage. IoB systems can also be used to monitor batteries remotely. This can help improve battery efficiency and extend battery life.

The IoB consists of three main components: battery systems, IoT gateway and cloud platform, and two additional components, i.e., BMS and wireless module, which are integrated within the battery systems.

First, battery systems form the fundamental layer of the IoB architecture, particularly in the context of electric vehicles. Second, the wireless module is a critical component of the IoB system for electric vehicles. Third, the IoT gateway links the wireless module and the cloud platform, ensuring secure and efficient data transmission. Finally, the cloud platform provides a centralized hub to store, process and analyze battery data collected from various electric vehicles.

Machine learning is a powerful tool that can be used to improve the efficiency and effectiveness of IoB systems. By analyzing data and learning from patterns, machine learning can help IoB systems make more informed decisions about battery management, charging, usage, and vehicle management.

This can lead to better battery performance, longer range and reduced costs for electric vehicle owners. Machine learning approaches can be broadly classified into three main categories: supervised, unsupervised, and boosting.


The various challenges associated with implementing IoB in electric vehicles. Credit: Green Energy and Intelligent Transportation

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The various challenges associated with implementing IoB in electric vehicles. Credit: Green Energy and Intelligent Transportation

The IoB presents numerous promising opportunities, particularly for the electric vehicle industry. This digital technology promises benefits such as continuous battery health checks, better energy management, health estimation, prediction and fault diagnosis, significantly transforming the landscape of electric vehicle technology.

However, implementing IoB in electric vehicles presents a number of challenges. The innovative integration of IoT technologies within the BMS of electric vehicles presents a wide range of challenging issues that must be thoroughly addressed for the technology to reach a reliable state and widespread use.

One of the most prominent concerns in the IoB space is the security of battery data. Another important challenge lies in the compatibility between different systems. Finally, the large-scale application of IoB in electric vehicles comes with its own set of technical complexities.

In the future, more research and development will be needed to fully realize the potential of the IoB and optimize battery usage in electric vehicles. Future efforts should address challenges such as data security and system compatibility.

Additionally, research should explore the potential role of artificial intelligence and machine learning in improving the efficiency and effectiveness of IoB systems. The IoB has the potential to transform the electric vehicle industry, but realizing this potential will depend on addressing these challenges and taking advantage of the opportunities it offers.

More information:
Heng Li et al, IoB: Internet of Electric Vehicle Batteries: Architectures, Opportunities and Challenges, Green energy and smart transportation (2023). DOI: 10.1016/j.geits.2023.100128

Provided by green energy and smart transportation

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