A novel technique for modelling the state of charge of lithium ion batteries using artificial neural networks

IEE Conference Publication

Volumn , Issue 484, 2001, Pages 174-179

  Grewal, S ^a   Grant, D A ^a  

^a UNIVERSITY OF BRISTOL   (United Kingdom)

Author keywords

GSM standard; Lithium ion batteries; Neural network

Indexed keywords

BACKPROPAGATION; CALCULATIONS; CELLULAR TELEPHONE SYSTEMS; CHARGING (BATTERIES); COMPUTER SIMULATION; FEEDFORWARD NEURAL NETWORKS; FUNCTIONS; GLOBAL SYSTEM FOR MOBILE COMMUNICATIONS; LEARNING ALGORITHMS; MATHEMATICAL MODELS; MULTILAYER NEURAL NETWORKS;

LITHIUM ION BATTERIES; SIGMOID FUNCTION; SOFTWARE PACKAGE MATLAB; STATE OF CHARGE;

LITHIUM BATTERIES;

EID: 0035714692     PISSN: 05379989     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

1. A PSPICE macromodel for lithium ion batteries
2. Energy gauge for lead-acid batteries in electric vehicles
3. Prediction of remaining battery discharge capacity by neural networks and it's display
4. The available capacity computation model based on artificial neural network for lead-acid batteries in electric vehicles
5. Artificial neural network simulation of battery performance
6. Battery pack state of charge estimator design using computational intelligence approaches
7. Stochastic battery discharge in portable communication devices
8. A microcontroller controller battery fuel gauge and charger