Samsung Electronics Co., Ltd.

Piyush Tagade

Krishnan Seethalakshmi Hariharan

Tae Won Song

Rajkumar Subhash Patil

Ankit Yadu

Krishnan Seethalakshmy Hariharan

Aravinda Reddy Mandli

Jason Michael Battle

Ashish Khandelwal

Periyasamy Paramasivam

Sanoop Ramachandran

Subramanian Swernath Brahmadathan

Jeonghoon Jo

Arijit Guha

S Krishnan Hariharan

Shanthi Pandian

Dough Heun Kang

Parampalli Shashishekara Adiga

The present disclosure provides a method and a system for improving the state of health (SoH) of rechargeable batteries. The method comprises receiving a plurality of battery parameters during charging of a battery and estimating model parameters of the battery using a mathematical model. The method also comprises comparing the estimated model parameters of the battery and the received battery parameters to determine degradation parameters of the battery in real-time, determining new charging current profile of the battery based on the degradation parameters of the battery, and applying the determined new charging current profile to the battery for improving the SoH of the battery.

Method and system for improving state of health of rechargeable batteries

The embodiments herein disclose a method and system for designing molecules by using a machine learning algorithm. The method includes representing molecular structures included in a dataset by using a Simplified Molecular Input Line Entry System (SMILES), where the SMILES uses a series of characters, converting a SMILES representation of the molecular structures into a binary representation, pre-training a stack of Restricted Boltzmann Machines (RBMs) by using the binary representation of the molecular structures, constructing a Deep Boltzmann Machine (DBM) by using the stack of the RBMs, determining limited molecular property data for a subset of the molecule structures in the dataset, training the DBM with the limited molecular property data, combining the pre-trained stack of the RBMs and the trained DBM in a Bayesian inference framework, and generating a sample of molecules with target properties by using the Bayesian inference framework.

Method and system for performing molecular design using machine learning algorithms

Disclosed is an electronic device including a battery, a charging circuit configured to charge the battery, a measurement circuit configured to measure a state of the battery, and a processor configured to be electrically connected with the battery, the charging circuit, and the measurement circuit, to charge the battery using the charging circuit set by a first charging parameter, determine state information corresponding to a state of the battery based on data associated with the state of the battery obtained using the measurement circuit, determine a second charging parameter for reducing loss of a capacity of the battery based on the state information, and charge the battery using the charging circuit set by the second charging parameter.

Electronic device for changing charging parameter depending on state of battery and control method thereof

Disclosed is a battery state of charge (SOC) determining method and a battery managing apparatus that acquires a stochastic reduced order model (SROM) and a mean using battery conservation equations acquired based on a stochastic Pseudo 2-dimensional electrochemical thermal (P2D-ECT) model, measures state information, and assimilates the state information with the SROM and the mean to determine an accurate SOC at a relatively low calculation cost.

Method of determining state of charge of battery and battery managing apparatus

Embodiments herein provide a method and electronic device for detecting an internal short circuit in a battery. The method includes obtaining, by a battery management system, battery gauge data. Further, the method includes estimating, by the battery management system, an internal resistance of the battery using the battery gauge data. Furthermore, the method includes detecting, by the battery management system, the internal short circuit in the battery by comparing a change in the internal resistance with a pre-defined resistance change threshold value.

Method and electronic device for detecting internal short circuit in battery

A method includes estimating an average concentration of ions in electrodes of a battery and estimating a state-of-charge (SOC) of the battery by Coulomb counting, correcting the ion concentration based on a difference in predicted and measured cell voltages, and correcting the Coulomb counting SOC based on a relation between SOC estimated by Coulomb counting and the average concentration, and the difference in the predicted and measured cell voltages.

Method for real time correction of ion concentration and Coulomb counting state-of-charge (SOC) in battery

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Bengaluru, India

Piyush Tagade