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Simulation Method for Extended-Range Electric Vehicle Battery State of Charge and Energy Consumption Simulation based on Driving Cycle
Kusuma C.F.a, Budiman B.A.a, Nurprasetio I.P.a
a Institut Teknologi Bandung, Faculty of Mechanical and Aerospace Engineering, 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]© 2019 IEEE.The battery state of charge and energy consumption are two parameters which are characterized by the usage of an extended-range electric vehicle (EREV). Those two parameters should be simulated in order to design the EREV properly according to different design needs, therefore a simulation method is needed. This work tries to establish a simulation method for the simulation of EREV battery state of charge and energy consumption. The EREV propulsion system modeling required for the simulation method are obtained from the general and electric vehicle engineering. Driving cycle data is also involved in the simulation. After the simulation method has been established, this work also validates the established simulation method with two validation methods. The validation step shows that the established simulation method is able to produce satisfying energy consumption simulation results. However, this simulation method needs to be provided with data and modeling, which comply with the simulated EREV, in order to produce a more satisfying battery state of charge simulation result. This work offers an initial perspective of EREV simulation, especially for the battery state of charge and energy consumption. The established simulation method can hopefully contribute to the design process of EREVs in the future.[/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]Battery state of charge,Driving cycle,EREV,Extended-range electric vehicles,method,Propulsion system,simulation[/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]battery state of charge,driving cycle,energy consumption,EREV,extended-range electric vehicle,method,propulsion system,simulation[/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]ACKNOWLEDGMENT This research is partially funded by LPDP through RISPRO program and USAID through Sustainable Higher Education Research Alliances (SHERA) program with grant number IIE00000078-ITB-1.[/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/ICEVT48285.2019.8993963[/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]