Abstract
The State of Charge (SOC) estimation is a significant issue for safe performance and the lifespan of Lithium-ion (Li-ion) batteries. In this paper, a Robust Adaptive Online Long Short-Term Memory (RoLSTM) method is proposed to extract SOC estimation for Li-ion Batteries in Electric Vehicles (EVs). This real-time, as its name suggests, method is based on a Recurrent Neural Network (RNN) containing Long Short-Term Memory (LSTM) units and using the Robust and Adaptive online gradient learning method (RoAdam) for optimization. In the proposed architecture, one sequential model is defined for each of the three inputs: voltage, current, and temperature of the battery. Therefore, the three networks work in parallel. With this approach, the number of LSTM units are reduced. Using this suggested method, one is not dependent on precise battery models and can avoid complicated mathematical methods. In addition, unlike the traditional recursive neural network where content is re-written at any time, the LSTM network can decide on preserving the current memory through the proposed gateways. In that case, it can easily transfer this information over long paths to receive and maintain long-term dependencies. Using real databases, the experiment results illustrate the better performance of RoLSTM applied to SOC estimation of Li-Ion batteries in comparison with a neural network modeling and unscented Kalman filter method that have been used thus far.
Highlights
Received: 14 December 2020For over 100 years, automobiles have been used for transportation of humans, goods, etc. and, in this way, reformed traveling around the world
As can be seen in these figures, the State of Charge (SOC) estimate achieved by the Robust Adaptive Online Long Short-Term Memory (RoLSTM) is quite smooth
These results show that the maximum error of SOC estimation for Li f ePO4 battery by the RoLSTM method for all datasets with fixed ambient is less than 2% and for different ambient is less than 2.5%
Summary
Received: 14 December 2020For over 100 years, automobiles have been used for transportation of humans, goods, etc. and, in this way, reformed traveling around the world. World Health Organization (WHO), in 2000, fuel vehicles produce 34% of nitrogen dioxide discharged into the environment. Reacting with humidity in the air, nitrogen dioxide makes nitric acid, which causes severe decay of metals. It causes thick fog and drastically reduces field of view. This molecule has a critical negative footprint on plant growth and a greenhouse effect. Nowadays, using electric vehicles (EVs) as an alternative to diesel- and petrol-powered cars is highly regarded. In this context, a high-tech battery is a crucial element for EVs
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