Instrumentation & Measurement Magazine 24-3 - 95

due to multi-directional data collection, which can lead to the
network slowdown. Fig. 4 shows the schematic of WBMS proposed by Linear Technologies Corporation.
It is mentioned in [4] that IoT can provide a reliable solution
to the BMS problem. IoT devices containing a communication component and a system-on-chip Integrated Circuit (IC)
form the central element of a WBMS. The communication subsystem uses IoT protocols and IoT gateways to communicate
with external systems, such as the converter and the internal modules. The IC, which is used for balancing and data
acquisition, measures the current, voltage, and temperature
of battery cells at a given time and balances the voltage if required. In this method, the IoT nodes elect a leader module by
executing a distributed algorithm. The leader node collects
the data, which includes the battery power and available capacity of each module node, and sends the aggregated results
to the converter to decide whether to continue or stop the battery charging process. The leader node is selected at a specific
time through a unique algorithm, known as the Leader Election Algorithm (LEA), which is executed simultaneously by
all nodes. Every node uses a random number to set a unique
rank and reads the SoC of the current module. Then, the nodes
broadcast the message over a communication medium and
receive the message from other module nodes. Once the broadcast message is received, the nodes check the SoC value and
the rank to elect a local leader in their communication range.
Certain local leaders then repeat the same process and choose
a global leader. Moreover, if the existing leader fails, other
nodes can elect a new leader by re-executing the algorithm.
The information about the new leader is then communicated
to all other nodes. The leader node uses a special IoT protocol,

called Message Queuing Telemetry Transport (MQTT), which
helps to estimate the SoC of a battery bank. Furthermore, this
protocol assists in module-to-module communication. It is expected that the IoT gateway can produce a large amount of
data. Hence, it is important to store, process, and quickly aggregate the data. This method provides access to the cloud
using various user interfaces. The data that is stored temporarily in the memory is sent to the cloud database, which uses
different TCP/IP protocols. The proposed IoT wireless system
supported by cloud-computing is quite efficient in managing
a battery. It can minimize the wire-harness issues and provides
higher battery module scalability.

Monitoring and Fault Diagnosis
The IoT technology along with cloud computing resources
can potentially revolutionize the BMS as they are cost-effective and can efficiently determine the health of a battery. They
are also adaptable and scalable and can ensure reliability and
security in Lithium-ion BESSs [35]. In [35], the main goal is to
design a cyber-physical BMS for Lithium-ion batteries by utilizing IoT sensors and cloud computing methods. The study
incorporates WMMS and a platform for fault diagnosis. In the
WMMS, IoT sensors measure the current, voltage, and temperature of a battery at a given time. As the nodes cannot store
a large amount of data, the data is sent to a cloud server using
TCP/IP protocol via an IoT gateway where the data is stored in
a cloud data storage. The MMS, on the other hand, receives the
results of health monitoring processes from the Cloud Battery
Management Platform (CBMP). The CBMP is used to support
the battery health monitoring system to detect any defects in
battery cells. Fig. 5 shows the proposed CBMP for BESS in [35].

Fig. 5. The proposed CBMP for BESS in [35].
May 2021

IEEE Instrumentation & Measurement Magazine 95

Instrumentation & Measurement Magazine 24-3

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