Global Organization
In this research, we proposed a prediction method for voltage and lifetime of lead–acid battery. The prediction models were formed by three kinds mode of four-points consecutive voltage and time index.The first mode was formed by four fixed voltages value during four weeks, namely M1.
Remaining useful life (RUL) prediction of lithium-ion batteries plays an important role in battery failure prediction and health management (PHM). By accurately predicting the RUL of the battery, the…
Analysis of RUL predictions To verify the method presented, another UNL50-2 type lead acid battery was cycled to the end of its life. The battery's capacity reduced to 60% of the rated capacity according to the manual until the 116th cycle, which is the end of life (EOL), and the capacity of each cycle was recorded before that.
To add more battery's mechanism information to PF-based RUL prediction methods is a potential resolution to push forward this technology. The work presents a new method for battery's RUL prediction by incorporating electrochemical model to the Particle Filtering framework, taking lead-acid battery for example.
Since lead–acid batteries are still the main source of electricity in many vehicles, their life prediction is a very important issue. This paper uses MLP and CNN to establish a voltage decay model of lead–acid battery to predict battery life. First, 10 prediction models are built through 10 data training sets and tested using one test set.
The selection of cycling aging features is particularly important for predicting the RUL of lithium-ion batteries. However, the number and basis for selecting these features vary among existing studies. It is well known that the more information contained in characteristic factors, the higher the accuracy of RUL prediction.
RUL is a critical predictive maintenance metric of a lead-acid battery. It is an estimate of the time a battery can continue operating while meet-ing performance …
Here we highlight three longstanding ''holy grail'' problems for battery state prediction where machine learning has the potential to make significant inroads: (1) holistic …
In this research, we proposed a prediction method for voltage and lifetime of lead–acid battery. The prediction models were formed by three kinds mode of four-points …
Accurate prediction of remaining useful life (RUL) can ensure the safety and reliability of power batteries during operation, reduce the failure rate and operating costs, and …
Electrified transportation systems are emerging quickly worldwide, helping to diminish carbon gas emissions and paving the way for the reduction of global warming possessions. Battery remaining useful life (RUL) …
Aiming at the prediction of the remaining discharge time of the battery, this paper comprehensively analyzes the influence of current intensity, voltage, and battery attenuation …
Remaining useful life (RUL) prediction of lithium-ion batteries plays an important role in battery failure prediction and health management (PHM). By accurately predicting the …
This work proposes and validates a reformulated equation which provides an accurate prediction of the runtime for single discharge applications using only the battery …
In this research, we proposed a prediction method for voltage and lifetime of lead–acid battery. The prediction models were formed by three kinds mode of four-points consecutive voltage and time ...
The experimental data demonstrate that the IF-GRU model proposed in this paper has higher prediction accuracy and convergence speed with a RMSE of 1.59% …
According to our research on lead–acid battery voltage prediction, we give the following conclusions and suggestions: (1) the selected prediction model has more input parameters such as CNN; (2) the input …
This work proposes and validates a reformulated equation which provides an accurate prediction of the runtime for single discharge applications using only the battery name plate information such ...
From the graphs, it is shown that the limited discharge voltage of a 12V/80Ah lead-acid battery changes with different load, the internal resistance value of a lead-acid …
Aiming at the prediction of the remaining discharge time of the battery, this paper comprehensively analyzes the influence of current intensity, voltage, and battery attenuation …
Semantic Scholar extracted view of "A lead-acid battery''s remaining useful life prediction by using electrochemical model in the Particle Filtering framework" by Chao Lyu et …
The remaining useful life (RUL) prediction is critical for the safe and reliable operation of lithium-ion battery (LIB) systems, which characterizes the aging status of the battery and provides ...
Predicting the lifetime of lead-acid batteries in applications with irregular operating conditions such as partial state-of-charge cycling, varying depth-of-discharge and …
Downloadable (with restrictions)! Accurate prediction of battery''s remaining useful life (RUL) is significant for the reliability and the cost of systems. This paper presents a new Particle Filter …
Lead acid (LA) batteries are still widely used in different small and large scale applications along with Lithium-ion (Li-ion), Nickel-Cadmium (NiCd) batteries [1] spite …
The prediction results show that in the aspect of predicting SOC of storage battery, the prediction accuracy of LM-BP neural network is higher than that of SVM and the training time is also ...
Accurate prediction of battery''s remaining useful life (RUL) is significant for the reliability and the cost of systems. This paper presents a new Particle Filter (PF) framework for …
According to our research on lead–acid battery voltage prediction, we give the following conclusions and suggestions: (1) the selected prediction model has more input …
This paper presents a battery management system for lead-acid battery banks used in e-vehicle. It is incorporated with a diagnostic, measurement, and monitoring system for …
Accurate prediction of remaining useful life (RUL) can ensure the safety and reliability of power batteries during operation, reduce the failure rate and operating costs, and …