Development of battery management systems (BMS) for electric vehicles (EVs) in Malaysia

Salehen, Puteh Melor Wesma; Su’ait, Mohd Sukor; Razali, Halim; Sopian, Kamaruzzaman

doi:10.1051/matecconf/20179001001

Cited by 9 publications

(5 citation statements)

References 7 publications

(9 reference statements)

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“…Electric vehicle batteries typically consist of the same types of battery cells connected in series and parallel. When these batteries are subjected to the same external excitation, the voltage change in the same type of battery should follow a normal distribution [34]. Hence, any battery unit that falls outside the probability range of the normal distribution can be considered anomalous.…”

Section: Lof Algorithmmentioning

confidence: 99%

Fault Diagnosis Method for Lithium-Ion Power Battery Incorporating Multidimensional Fault Features

Zhang,

Zheng,

Xing

et al. 2024

Energies

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Accurately identifying a specific faulty monomer in a battery pack in the early stages of battery failure is essential to preventing safety accidents and minimizing property damage. While there are existing lithium-ion power battery fault diagnosis methods used in laboratory settings, their effectiveness in real-world vehicle conditions is limited. To address this, fault diagnosis methods for real-vehicle conditions should incorporate fault characteristic parameters based on external battery fault characterization, enabling the accurate identification of different fault types. However, these methods are constrained when confronted with complex fault types. To overcome these limitations, this paper proposes a battery fault diagnosis method that combines multidimensional fault features. By merging different fault feature parameters and mapping them to a high-dimensional space, the method utilizes a local outlier factor (LOF) algorithm to detect anomalous values, enabling fault diagnosis in complex working conditions. This method improves the detection time by an average of 22 min compared to the extended RMSE method and maintains strong robustness while correctly detecting faults compared to other conventional methods.

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Section: Lof Algorithmmentioning

confidence: 99%

Fault Diagnosis Method for Lithium-Ion Power Battery Incorporating Multidimensional Fault Features

Zhang,

Zheng,

Xing

et al. 2024

Energies

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“…The research from [19][20][21][22] all proposed a real-world application for a battery monitoring system, with particular emphasis on its application in EVs. The system in [22] monitors the battery to detect dead cells, highlighting the significance of monitoring battery lifespan and safety.…”

Section: Electric Vehicle Battery Monitoringmentioning

confidence: 99%

Remote Low-Cost Web-Based Battery Monitoring System and Control Using LoRa Communication Technology

Isa,

Iqbal

2024

J. Electron. Electric. Eng.

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Batteries are a complex electrochemical device that exhibit non-linearity and stochastic behavior which rely upon the operational conditions and environmental factors, making battery monitoring a vital feature throughout its application. This paper introduces a novel web-based battery monitoring and control system that utilizes Long Range (LoRa) communication technology, an integral part of the Internet of Things (IoT). The system is implemented with the ESP32 microcontroller, with an emphasis on affordability in broader applications. The system provides comprehensive real-time online data by integrating a combination of multiple sensors. The proposed system seeks to address the limitations of existing communication technology by utilizing the benefits of LoRa, a technology that facilitates effective long-range, low-energy communication which makes it particularly well-suited for real-time monitoring applications. In addition, a control operation enables users to regulate crucial aspects of batteries, such as their charging and discharging. The research conducted a meticulous experimental evaluation of the proposed system at different operations, and the results successfully aligned with the main objective and aims of the research. The proposed system successfully enables real-time remote monitoring and user control, long-term data visualization through data logging, and assessment of battery conditions. Data logging was introduced to enhance the utilization of future battery evaluation, such as State-of-Charge (SOC), State-of-Health (SOH) and Remaining Useful Life (RUL). As a result, the developed system makes it suitable for many applications requiring effective energy storage solutions, such as renewable energy and Electric Vehicle (EV) applications.

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“…The government of Malaysia has future plan to install 25,000 electric-vehicle charging stations throughout Malaysia by 2020 (Adnan, Nordin & Rahman, 2017), and to announce National Automobile Policy (NAP) 2014 to urge local automobile manufacturers to produce EEV (Chian, Aziati & Yusof 2017). Malaysia also already committed to reducing 40% greenhouse gas (GHG) emissions by the year 2020 with electric vehicle (EV) future innovation invention (Salehen et al, 2017;Schüller et al, 2017). According to a previous study (Schüller et al, 2017), gas driven vehicle (LPG) achieves the best results due to lower consumption costs.…”

Section: Energy Efficient Vehicles (Eev)mentioning

confidence: 99%

Challenges and Strategies of Malaysian Automotive: A Literature Review 2016-2018

Nazir

Shavarebi²

2019

JTMB

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With the increasing urbanization and the global population growth leads to high demand for mobility (Schüller et al., 2017). Global attention has been received by automobile industries in ASEAN for domestic and overseas competitiveness (Tai, 2016) lead to stiff global competition (Maarof & Mahmud, 2016). Due to strategically located in the center of ASEAN, Malaysia offers vast opportunities for global automotive and component manufacturers to set up manufacturing and distribution operations (

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Development of battery management systems (BMS) for electric vehicles (EVs) in Malaysia

Cited by 9 publications

References 7 publications

Fault Diagnosis Method for Lithium-Ion Power Battery Incorporating Multidimensional Fault Features

Fault Diagnosis Method for Lithium-Ion Power Battery Incorporating Multidimensional Fault Features

Remote Low-Cost Web-Based Battery Monitoring System and Control Using LoRa Communication Technology

Challenges and Strategies of Malaysian Automotive: A Literature Review 2016-2018

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