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State of charge estimation method for lithium battery using combination of coulomb counting and adaptive system with considering the effect of temperature
Purwadi A.a, Rizqiawan A.a, Kevin A.a, Heryana N.a
a School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2014 IEEE.The needs of good State of Charge (SOC) estimation method for lithium batteries are very high, not only useful for battery protection, preventing under-discharged, controlling the battery management system, and increasing the battery life, but also to increase the useable battery power. To make an SOC estimation method, second order Thevenin dynamic battery model is chosen, where the impedance values change in accordance with the SOC level. Hybrid method, which combine Coulomb Counting Method and Adaptive System Method, is chosen here. Coulomb Counting method suffers a weakness in term of initial SOC value determination, while Adaptive System Method with its ability to adjust with changes in the system will be a solution for the mentioned drawback. It can be shown that the proposed SOC estimation model is able to function properly and fairly represent the lithium battery characteristic. The method can be used not only on the specific lithium battery, but can be used in various lithium batteries by updating the its Look-up table block. Simulation and experiment have been done to verify the proposed method.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Coulomb counting method,Dynamic battery,Effect of temperature,Estimation methods,SOC estimations,State of charge,State-of-charge estimation,Value determination[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Adaptive System,SOC Estimation;, Coulomb Counting,State of Charge[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ICPERE.2014.7067233[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]