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Memoria Investigaciones en Ingeniería, núm. 26 (2024). pp. 202-212

https://doi.org/10.36561/ING.26.12

ISSN 2301-1092 • ISSN (en línea) 2301-1106 – Universidad de Montevideo, Uruguay

Este es un artículo de acceso abierto distribuido bajo los términos de una licencia de uso y distribución CC BY 4.0.

Para ver una copia de esta licencia visite https://creativecommons.org/licenses/by/4.0/

Towards Sustainable Energy Storage: A Low-Cost IoT Solution for Real-time

Monitoring of Lead-Acid Battery Health

Hacia el almacenamiento de energía sostenible: una solución de IoT de bajo costo

para el monitoreo en tiempo real del estado de las baterías de plomo-ácido

Rumo ao armazenamento de energia sustentável: uma solução IoT de baixo custo

para monitoramento em tempo real da saúde da bateria de chumbo-ácido

Sadiq Ur Rehman

(*), Halar Mustafa

, Muhammad Ahsan Shaikh

, Shahzor Memon

Recibido: 13/03/2024 Aceptado: 20/05/2024

Summary. - This research article introduces a microcontroller-based prototype system called the Battery Health

Monitoring System (BHMS), designed to evaluate the health and condition of lead-acid batteries. The focus of the

study is on utilizing the Internet of Things (IoT) for real-time battery monitoring. The system incorporates various

sensors to track and record critical parameters such as current, voltage, power drain, state of charge (SOC), temperature,

and overall battery health. These sensors are configured to trigger an alert when any monitored parameters fall below

predefined values. The study aims to validate the effectiveness of the proposed low-cost system in real-time monitoring

of lead-acid batteries.

Keywords: Lead-acid battery, Temperature, IoT, ESP8266.

(*) Corresponding Author

Ph.D., Assistant Professor, FEST, Hamdard University (Pakistan), sadiq.rehman@hamdard.edu.pk,

ORCID iD: https://orcid.org/0000-0002-6308-450X

M.E, Lecturer, FEST, Hamdard University (Pakistan), halar.mustafa@hamdard.edu.pk,

ORCID iD: https://orcid.org/0000-0002-7021-5010

Ph.D., Lecturer, FEST, Hamdard University (Pakistan), muhammad.ahsan@hamdard.edu.pk,

ORCID iD: https://orcid.org/0000-0003-2408-5689

M.E. Assistant Professor, FEST, Hamdard University (Pakistan) Shahzor.memon@hamdard.edu.pk,

ORCID iD: https://orcid.org/0000-0003-3555-628X

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Resumen. - Este artículo de investigación presenta un sistema prototipo basado en microcontrolador llamado

Sistema de monitoreo del estado de la batería (BHMS), diseñado para evaluar la salud y el estado de las baterías de

plomo-ácido. El objetivo del estudio es utilizar el Internet de las cosas (IoT) para monitorear la batería en tiempo

real. El sistema incorpora varios sensores para rastrear y registrar parámetros críticos como corriente, voltaje,

consumo de energía, estado de carga (SOC), temperatura y estado general de la batería. Estos sensores están

configurados para activar una alerta cuando algún parámetro monitoreado cae por debajo de los valores

predefinidos. El estudio tiene como objetivo validar la eficacia del sistema de bajo coste propuesto en el seguimiento

en tiempo real de baterías de plomo-ácido.

Palabras clave: Batería de plomo-ácido, Temperatura, IoT, ESP8266.

Resumo. - Este artigo de pesquisa apresenta um protótipo de sistema baseado em microcontrolador denominado

Battery Health Monitoring System (BHMS), projetado para avaliar a saúde e a condição de baterias de chumbo-ácido.

O foco do estudo está na utilização da Internet das Coisas (IoT) para monitoramento da bateria em tempo real. O

sistema incorpora vários sensores para rastrear e registrar parâmetros críticos, como corrente, tensão, consumo de

energia, estado de carga (SOC), temperatura e integridade geral da bateria. Esses sensores são configurados para

disparar um alerta quando algum parâmetro monitorado cair abaixo dos valores predefinidos. O estudo visa validar

a eficácia do sistema de baixo custo proposto no monitoramento em tempo real de baterias de chumbo-ácido.

Palavras-chave: Bateria de chumbo-ácido, Temperatura, IoT, ESP8266.

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Introduction. - Batteries are critical in various applications, including automotive, renewable energy, and

telecommunication systems [1]. The failure of batteries can lead to significant consequences, including power outages,

equipment damage, and economic losses. Therefore, it is essential to monitor the health of batteries in real time to

ensure their optimal performance and prevent failure. Figure I show the market demand for lead acid batteries in the

general market.

Figure I. Market Distribution of Lead Acid Battery[2]

In lead-acid batteries, State of Charge (SOC), describes how charged the battery is right now about its maximum

capacity [3]. Usually, it is stated as a percentage, where 100% denotes a fully charged battery and 0% denotes a fully

discharged battery. For the battery to operate at its best and last as long as possible, it is imperative to monitor its state

of charge (SOC). A typical formula for calculating a 12V lead-acid battery's SOC can be written as;

SoC= 𝑅𝑒𝑚𝑎𝑖𝑛𝑖𝑛𝑔 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦

𝑓𝑢𝑙𝑙 𝑐ℎ𝑎𝑟𝑔𝑒 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦 (𝑇𝑒𝑚𝑝𝑒𝑟𝑎𝑡𝑢𝑟𝑒, 𝑃𝑟𝑒𝑠𝑒𝑛𝑡 𝑐ℎ𝑎𝑟𝑔𝑒 𝑜𝑟 𝑑𝑖𝑠𝑐ℎ𝑎𝑟𝑔𝑒 𝑟𝑎𝑡𝑒) Eq (1)

The opposite of the SOC, the State of Discharge (SOD) in lead-acid batteries indicates how much of the battery's

capacity has been utilized.

SOD=100%−SOC Eq (2)

With the advent of the Internet of Things (IoT) [4-5], battery health monitoring systems can now be designed and

implemented at low costs with increased efficiency.

This research paper focuses on designing and implementing a low-cost battery health monitoring system using IoT for

real-time monitoring of lead-acid batteries. Since lead acid batteries have high reliability and low maintenance

requirements, they are widely used in various applications. The major issue with lead-acid batteries is the problem of

sulfation [6], water loss, and corrosión. Careful monitoring of these batteries is required to prevent failure and enhance

lifespan. In this article, we proposed the battery health monitoring system consists of IoT based system that collects

data from various sensors attached to the lead-acid batteries. The sensors are responsible for calculating the parameters

like temperature, voltage, current, and electrolyte level, to provide the status of the battery's health. Collected data is

then transmitted to the IoT platform for real-time monitoring and analysis.

In the proposed system, we have used all the components that are easily available in the market to reduce cost. Even

the IoT platform (ThinkSpeak) is used as open-source software. The real-time monitoring features of the system allow

users to recognize possible battery problems and take preventative measures before damage is done.

Literature Review.- Lead acid batteries are one of the essential power sources that are extensively used in various

industries, these industries include automotive, telecommunications, power generation, distribution, etc [7]. Hence it

is important to have an effective battery system. The problem with lead acid batteries is rated to their cost (expensive),

and their continuous usage may cause performance degradation. There is also a recycling process issue with the lead

acid batteries which cause damage to the environment [8]. As a result, it is important to keep vigilant in the management

and handling of lead acid batteries to minimize adverse effects and increase their lifespan.

There has been a lot of research work done in the field of monitoring the health of lead-acid batteries. Extensive work

is presently related to the battery management systems (BMS) required for lead acid batteries. Authors in [9]

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demonstrate how to calculate the state of charge (SoC) and introduce the concept of the battery management system

(BMS) that is used for systems like uninterruptible power supplies (UPS), hybrid electric vehicles (HEVs), and electric

cars (EVs). No concept of real-time monitoring was present in this research work. The work on the accuracy of battery

monitoring circuits for portable communication devices is proposed in [10]. However, this system’s accuracy is subject

to debate because when all the parameters are considered, it produces an error margin of up to 10%. Working on

parameters like temperature, voltage, current, and SoC was done in [11] with the analysis of battery discharging

parameters. This research provided the key importance of monitoring all batteries in a battery bank to keep the ideal

operating levels and circumstances. Discussion and development tendencies of electric vehicle (EV) batteries were

done in [12], in these articles author emphasizes the importance of the BMS in both electric and hybrid vehicles. This

study describes how BMS features including cell balancing, charge management, and state monitoring are combined

to guarantee dependable and safe battery operation. However, again in this work, real real-time monitoring feature was

not included. In [13], the authors address the present issues with BMS and emphasize the significance of assessing a

battery's condition, including its longevity, health, and charge. Through an examination of the most recent methods for

battery condition evaluation, it also addresses upcoming issues and possible fixes for BMS.

Today's electric vehicles prefer lithium-ion (Li-ion) batteries for energy storage due to their high energy density, strong

output, extended lifespan, low self-discharge rate, and lack of memory effect [14]. However, a well-designed BMS is

crucial to ensuring safety, dependability, performance optimization, and cost-effectiveness while lowering

manufacturing complexity and weight [15]. Table 1 represents the guide for the common battery used worldwide.

The transfer of data between controllers and sensors has led to the development of wireless Battery Management

Systems (WBMSs). These systems alleviate wiring issues and allow for more flexible placement of battery modules.

Utilizing 5G or 4G networks [16-18] along with an IoT gateway, WBMSs employ IoT protocols (such as those in

energy management systems or converters) to directly connect with cloud support servers for tasks like fault

diagnostics and battery state monitoring.

Table I. Pros and cons of common battery

In this paper, an IoT-based prototype model for real-time lead acid battery monitoring is provided. The objective is

accomplished by taking into account variables like temperature, voltage, current, power, and SOC, which are the

indicators of the battery's state of health. It is important to note that the proposed prototype is designed to accommodate

various capacities of 12V lead acid batteries, allowing versatility in its application.

Proposed system model.- The proposed system monitors the voltage, current, power utilized, state of charge (SoC),

health, and temperature of a lead-acid battery. The gathered data is sent to the IoT platform Thingspeak using the

ESP8266 [19] module, which is programmed with Arduino software. Arduino [20] is used to store and handle the data

generated by sensors. A voltage division circuit is used with an ACS712 sensor [21] to measure the voltage; it divides

the 12V from the lead-acid battery into 8.7V and 3.3V, with the 3.3V input going to the ESP8266 module.

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Figure II. System Block Diagram

The battery's voltage can be converted to a percentage to calculate the State of Charge (SoC). Since it is difficult to

measure the battery's interior temperature, the external temperature is instead monitored. A DHT 11 sensor [22] is used

for this. Thingspeak is used to monitor all of these characteristics, and updates are made in real-time every 15 seconds.

This proposed system can be put in remote locations, reducing the need for periodic power management system

maintenance. To achieve the claimed functionality, the component used in the proposed system model can be seen in

Figure III.

Figure III. Components for the prototype model

The voltage method used in this proposed prototype uses voltage analysis rather than current measurements to

indirectly derive the State of Charge (SoC). Thingspeak provides temperature, current, voltage, battery health, and

state of charge (SoC) data of the battery in a graphical format, facilitating remote monitoring via an IoT platform. In

this model, the load attached to the battery is a 12V DC fan.

Results.- After installing the Arduino software, the libraries for the DHT 11 sensor, ZMPT101B, ACS712, and

ESP8266 were downloaded. The coding for the proposed system model was completed using the Arduino software,

incorporating mathematical formulas to determine the SOC% from voltage data. Additionally, the calculation of power

utilized was performed using the formula provided in equation (3).

Power = Voltage x Current Eq (3)

The ESP8266 transmits all the sensor data to Thingspeak, an IoT platform, for monitoring. When there is a change in

battery current and voltage due to the load of a 12V DC fan, these changes can be observed in the graphs.

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Figure IV. Battery Charge Status.

Figure IV shows that battery charge status, readings were recorded at 10-minute intervals from 13:37 to 13:47. The

state of charge (SOC) indicates that 75% of the battery's charge remains when no load is connected. At 13:40, a 12V

DC fan was used as a load, causing the SOC graph to drop. Once the charge in the battery drops to 55%, the charging

circuit activates and increases the SOC to 98%. When the battery reaches this charge level, the charging stops,

resulting in a constant SOC graph as the DC fan is switched off at this time. After 1 minute, the fan switches on again,

causing the SOC to drop from 98%. Figure V shows the change in voltage due to the resistive load. Notably, when

the voltage level drops to 10V at 21:10, the battery starts charging and remains in charging mode until it reaches

11.6V. The variation in voltage drop is due to the DC fan speed, which consumes more current, as shown in Figure

VI.

Our proposed system works perfectly and matches the theoretical results of power utilization in mW with the

simulation results obtained from Figures V and VI, as seen in Figure VII.

Figure V. Change in battery voltage concerning the resistive load.

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Figure VI. Change in battery Current concerning the resistive load.

Figure VII. Power is drawn from the battery.

Figure VIII. Change in battery surface temperature due to change in current.

Figure VIII illustrates the variation in the surface temperature of the battery during charging and discharging. This

temperature change results from fluctuations in the temperature of the acid inside the battery that stores the charges.

Additionally, as the temperature rises, the battery's health deteriorates, as depicted in Figure IX. The battery's health

is determined using the formula provided in equation (4).

SoH = 𝑓𝑢𝑙𝑙 𝑐ℎ𝑎𝑟𝑔𝑒 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦 (25𝐶, 𝐷𝑒𝑠𝑖𝑔𝑛 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 𝑐ℎ𝑎𝑟𝑔𝑒 𝑜𝑟 𝑑𝑖𝑠𝑐𝑎𝑟𝑔𝑒 𝑟𝑎𝑡𝑒)

𝐷𝑒𝑠𝑖𝑔𝑛 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 Eq (4)

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Figure IX. Change in battery health.

There were some limitations encountered while testing this proposed system. One of the main challenges was

synchronizing data with the cloud. Additionally, obtaining a clear graph during variations in DC fan speed proved

difficult. The room temperature also affected the monitoring of the battery's surface temperature during charging and

discharging.

Conclusion.- Monitoring battery health is crucial for lead-acid batteries, and with the rise of wireless technology,

IoT has become a widely utilized feature in this prototype model. This functionality allows users to monitor lead-acid

battery parameters remotely and at any time. The proposed system model consists of basic components readily

available in local markets, and sensor coding to interface with the microcontroller is easily accessible online. Results

obtained from the model include State of Charge (SoC), voltage, current, power drained, surface temperature, and

battery health.

It's important to note that the performance of the proposed system may vary among different brands of lead-acid

batteries due to their unique discharge signatures. A notable aspect of the system is a 15-second delay before data is

uploaded to the cloud. It should be acknowledged that the system's accuracy may be compromised when dealing with

series and parallel combinations of batteries in power banks, as its optimization is geared toward single batteries.

Additionally, incorporating control features could be considered for future enhancements to this proposed system.

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Nota contribución de los autores:

1. Concepción y diseño del estudio

2. Adquisición de datos

3. Análisis de datos

4. Discusión de los resultados

5. Redacción del manuscrito

6. Aprobación de la versión final del manuscrito

SUR ha contribuido en: 1, 2, 3, 4 y 5.

HM ha contribuido en: 5 y 6.

MAS ha contribuido en: 5 y 6.

SM ha contribuido en: 5 y 6.

Nota de aceptación: Este artículo fue aprobado por los editores de la revista Dr. Rafael Sotelo y Mag. Ing. Fernando

A. Hernández Gobertti.