Figure - available from: Scientific Reports
This content is subject to copyright. Terms and conditions apply.
Source publication
Lithium-ion battery, a high energy density storage device has extensive applications in electrical and electronic gadgets, computers, hybrid electric vehicles, and electric vehicles. This paper presents multiple fault detection of lithium-ion battery using two non-linear Kalman filters. A discrete non-linear mathematical model of lithium ion batter...
Citations
... The Thevenin-based equivalent circuit consisting of internal series resistance and capacitance paralleled with another resistance is more accurate than that in Figure 12 [32]. The Thevenin-based capacitance is much larger than the battery-side capacitance C B [33]. From the control point of view, thus, the open-circuit voltage ⟨e 0 ⟩ in Figure 12 including the voltage drops in the Thevenin-based capacitance is the disturbance of the battery current control loop. ...
Integrating residential energy storage and solar photovoltaic power generation into low-voltage distribution networks is a pathway to energy self-sufficiency. This paper elaborates on designing and implementing a 3 kW single-phase grid-connected battery inverter to integrate a 51.2-V lithium iron phosphate battery pack with a 220 V 50 Hz grid. The prototyped inverter consists of an LCL-filtered voltage source converter (VSC) and a dual active bridge (DAB) DC-DC converter, both operated at a switching frequency of 20 kHz. The VSC adopted a fast DC bus voltage control strategy with a unified current harmonic mitigation. Meanwhile, the DAB DC-DC converter employed a proportional-integral regulator to control the average battery current with a dynamic DC offset mitigation of the medium-frequency transformer's currents embedded in the single-phase shift modulation scheme. The control schemes of the two converters were implemented on a 32-bit TMS320F280049C microcontroller in the same interrupt service routine. This work presents a synchronization technique between the switching signal generation of the two converters and the sampling of analog signals for the control system. The prototyped inverter had an efficiency better than 90% and a total harmonic distortion in the grid current smaller than 1.5% at the battery power of ±1.5 kW.
... The battery has a maximum voltage of 4.2V and a nominal voltage of 3.7V, likewise one or more Resistance-Capacitance (RC) networks are introduced to model the dynamic behavior of the battery. The Thevenin's equivalent circuit model of the battery [10,11,12,13] is a first order RC shown in Fig 5. The circuit consists of a voltage source, a resistor in series with an RC link. ...
... Step 8: Correct the system state and state variance matrix by Equations (32) and (33). ...
... In order to analyze the accuracy of the identification results, as well as the robustness and adaptiveness of the algorithm, the estimated terminal voltage can be obtained from the identified parameter values according to Equation (7) and compared with the actual terminal voltage. This algorithm is important for many applications, such as the estimation of the batteries' condition and fault diagnosis [33]. ...
State-of-charge (SoC) estimation is one of the core functions of battery energy management systems. An accurate SoC estimation can guarantee the safe and reliable operation of the batteries system. In order to overcome the practical problems of low accuracy, noise uncertainty, poor robustness, and adaptability in parameter identification and SoC estimation of lithium-ion batteries, this paper proposes a joint estimation method based on the adaptive extended Kalman filter (AEKF) algorithm and the adaptive unscented Kalman filter (AUKF) algorithm in multiple time scales for 18,650 ternary lithium-ion batteries. Based on the slowly varying characteristics of lithium-ion batteries’ parameters and the quickly varying characteristics of the SoC parameter, firstly, the AEKF algorithm was used to online identify the parameters of the model of batteries with a macroscopic time scale. Secondly, the identified parameters were applied to the AUKF algorithm for SoC estimation of lithium-ion batteries with a microscopic time scale. Finally, the comparative simulation experiments were implemented, and the experimental results show the proposed joint algorithm has higher accuracy, adaptivity, robustness, and self-correction capability compared with the conventional algorithm.
... Analogously, Bharathraj et al. [30] presented an electrochemical-thermal model to estimate battery state of power, which was further used for battery safety assessment. Sadhukhan et al. [31] developed a discrete nonlinear mathematical model to detect several battery safety issues, including overcharge, overdischarge, and short circuit. Li et al. [32] clarified the developing process from ISC occurrence to thermal runaway in a complex mechanical abuse environment using a three-dimensional two-way coupled mechanicalelectrochemical-thermal model. ...
Detecting battery safety issues is essential to ensure safe and reliable operation of electric vehicles (EVs). This
paper proposes an enabling battery safety issue detection method for real-world EVs through integrated battery
modeling and voltage abnormality detection. Firstly, a battery voltage abnormality degree that is adaptive to
different battery types and working conditions is defined. Then an integrated battery model is developed
by combining an electrochemical model, an equivalent circuit model (ECM), and a data-driven model to
evaluate the normal voltage. To ensure normality of input current, a current processing model is presented. The
performance of the proposed scheme is examined under random loading profiles using operating data collected
from real-world EVs. The results show that the integrated battery model can precisely predict normal battery
terminal voltage, with mean-squared-errors of 1.034e−4 𝑉 2, 7.221e−5 𝑉 2, and 4.612e−5 𝑉 2 for driving, quick
charging, and slow charging, respectively. The accuracy in classifying faulty and normal batteries is verified
based on the operating data collected from 20 EVs.
... Adaptive Kalman filter. The KF is essentially a recursive form of a state-optimal estimation algorithm, which is widely used in linear systems due to its simplicity and high accuracy [20][21][22] . The noise covariance matrices Q and R must be known in the conventional KF. ...
This paper focuses on designing a power allocation strategy for a fuel cell ship. The performance of the fuel cell varies during operation, so a power allocation strategy considering fuel cell performance differences is proposed, which consists of two layers. In the first layer, the maximum power and maximum efficiency of each fuel cell system (FCS) are updated in real-time with an online parameter identification model, which is composed of the fuel cell semi-empirical model and adaptive Kalman filter. The second layer takes the state of charge of the battery energy storage system, the maximum power, and the maximum efficiency as inputs for power allocation. Compared with the equal allocation strategy and daisy chain strategy, the total hydrogen consumption reduces by 5.3% and 15.1% and the total output power of the FCS with poor performance reduces by 14.1% and 15.7%. The results show that the proposed method can improve the efficiency of the ship power system and reduce the operational burden of the FCS with poor performance.
... The battery has a maximum voltage of 4.2V and a nominal voltage of 3.7V, likewise one or more Resistance-Capacitance (RC) networks are introduced to model the dynamic behavior of the battery. The Thevenin's equivalent circuit model of the battery [10,11,12,13] is a first order RC shown in Fig 5. The circuit consists of a voltage source, a resistor in series with an RC link. ...
Water pumps, being the most essential part of any irrigation system require fuel or electricity to be operated. Thefuel is often expensive, and majority of rural areas are not connected to the grid. This necessitated the need foran alternative source of energy to power the pumps. Solar energy is one of the most easily accessible forms ofenergy and has the advantages of being environmentally friendly and durable. The energy is also in abundanceand readily available. A key concern is the high cost of batteries to store the solar energy. This paper analyses theperformance of solar irrigation system using recycled laptop batteries. The use of recycled laptop batteries is expectedto cut the cost of deep-cycle batteries by more than 60%. Experimental results have shown that the recycledlithium-ion batteries can effectively power irrigation pump hence, can handle the irrigation process satisfactorily.
Renewable energy penetration and distributed generation are key for the transition towards more sustainable societies, but they impose a substantial challenge in terms of matching generation with demand due to the intermittent and unpredictable nature of some of these renewable energy sources. Thus, the role of energy storage in today’s and future electricity markets is undisputed. Batteries stand out among the different alternatives for energy storage. The R&D effort into different battery chemistries contributes to reducing the investment associated with battery systems. However, optimizing their operation according to the users’ and the electricity markets’ needs is the turning point to finally make these systems attractive. This review delves into the topic of battery management systems from a battery-technology-independent perspective, and it also explores more fundamental but related aspects, such as battery modeling or state estimation. The techno-economic part of battery energy storage systems is also covered in this document to understand their real potential and viability.
