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Real Time ÃæÀü½Ä ¸®Æ¬ÀÌ¿Â ÃæÀü ÃßÁ¤±â HEVs/EVs-A¿¡ ¹èÅ͸® ºñ±³¿¬±¸
Real Time ÃæÀü½Ä ¸®Æ¬ÀÌ¿Â ÃæÀü ÃßÁ¤±â HEVs/EVs-A¿¡ ¹èÅ͸® ºñ±³¿¬±¸
  • ÀúÀÚNicolae Tudoroiu, Mohammed Zaheeruddin, Roxana-Elena Tudoroiu Àú
  • ÃâÆÇ»ç¾ÆÁø
  • ÃâÆÇÀÏ2020-07-13
  • µî·ÏÀÏ2020-12-21
º¸À¯ 1, ´ëÃâ 0, ¿¹¾à 0, ´©Àû´ëÃâ 8, ´©Àû¿¹¾à 0

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Estimating the state of charge (SOC) of Li-ion batteries is an essential task of
battery management systems for hybrid and electric vehicles. Encouraged by some
preliminary results from the control systems field, the goal of this work is to
design and implement in a friendly real-time MATLAB simulation environment two
Li-ion battery SOC estimators, using as a case study a rechargeable battery of 5.4
Ah cobalt lithium-ion type. The choice of cobalt Li-ion battery model is motivated
by its promising potential for future developments in the HEV/EVs applications.
The model validation is performed using the software package ADVISOR 3.2,
widely spread in the automotive industry. Rigorous performance analysis of both
SOC estimators is done in terms of speed convergence, estimation accuracy and
robustness, based on the MATLAB simulation results. The particularity of this
research work is given by the results of its comprehensive and exciting
comparative study that successfully achieves all the goals proposed by the research
objectives. In this scientific research study, a practical MATLAB/Simscape battery
model is adopted and validated based on the results obtained from three different
driving cycles tests and is in accordance with the required specifications. In the
new modelling version, it is a simple and accurate model, easy to implement in
real-time and offers beneficial support for the design and MATLAB implementation
of both SOC estimators. Also, the adaptive extended Kalman filter SOC estimation
performance is excellent and comparable to those presented in the
state-of-the-art SOC estimation methods analysis.

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Á¦ 1Æí : SIMULINK ±âº»Æí
1.1 SIMULINKÀÇ ½ÃÀÛ 1
ºí·ÏÀÇ ¿¬°á 5
ºí·Ï ÆĶó¹ÌÅÍÀÇ ¼³Á¤ 7
½Ã¹Ä·¹À̼ǠÆĶó¹ÌÅÍ (Configuration Parameters)ÀÇ ¼³Á¤ 8
½Ã¹Ä·¹À̼ÇÀÇ ¼öÇà 9
ºí·Ï ÆĶó¹ÌÅÍÀǠǥ½Ã 9
º¹¼ö µ¥ÀÌÅÍÀǠǥ½Ã 11
2.2 µ¿Àû ½Ã¹Ä·¹À̼Ǡ13
ÀÌÂ÷ ¹ÌºÐ¹æÁ¤½Ä 17
¼±Çü »óź¯¼ö ¸ðµ¨ 23
DC ¸ðÅÍÀÇ ½Ã¹Ä·¹À̼Ǡ24
ÇÔ¼ö ºí·ÏÀÇ »ç¿ë 29
Â÷ºÐ¹æÁ¤½Ä(difference equation)ÀÇ ¸ðµ¨¸µ 34
Subsystem(ºÎ½Ã½ºÅÛ)ÀÇ ±¸¼º 37

Á¦ 2Æí : ¿¬±¸³í¹®

1. Introduction 41
2. Lithium-Ion Battery-Cell Modelling and Validation 42
3. FDDI estimation techniques. 44
4. Li-Ion Co Battery State of Charge Estimation Algorithms 61
5. Real-Time MATLAB Simulation Results 66
6. Discussions 77
7. Conclusions 79
8. References 85

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