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Rasa-Powered Conversational AI Framework for Intelligent Electric Vehicle Trip Planning and Energy Management

Indonesian Journal of Electical Engineering and Informatics (IJEEI) · Vol. 13 No. 4 (2025) · pp. 911–922

DOI
10.52549/ijeei.v13i4.6553
ISSN
2089-3272, 2089-3272
Published
2025-12-01
Publisher
IAES Indonesian Section
Language
en

Abstract

The rapid growth of Electric Vehicles (EVs) calls for intelligent solutions to optimize grid stability and enhance user experience. This paper proposes a geo-optimized, user-centric EV management system integrating open-source geospatial tools with Rasa-based Natural Language Understanding (NLU). Through an interactive conversational interface, EV owners receive real-time trip planning recommendations based on parameters such as State of Charge (SoC), charging point availability, and route efficiency. The system utilizes APIs for real-time geolocation, charging station data, and Battery Management System (BMS) insights to determine optimal charging locations, durations, and trip costs. Extensive testing demonstrates improved energy management and route planning efficiency, highlighting the system’s potential for smart and sustainable EV infrastructure development.

Keywords

Collaboration network of the authors

34 authors · 131 co-authorship links

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Koneru Lakshmaiah Education Foundation
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Malligunta Kiran KumarKoneru Lakshmaiah Education Foundation3
G. Anjali DeviAffiliation unknown2
Swapna GanapaneniAffiliation unknown2
L. SirisaiahAffiliation unknown2
Lokesh KothaAffiliation unknown2
Subhash ManchikantiAffiliation unknown2
Venu YarlagaddaAffiliation unknown1
N. KavithaAffiliation unknown1
Chava Sunil KumarAffiliation unknown1
G. NaveenAffiliation unknown1
Swetha MareddyAffiliation unknown1
S. Venkata Rami ReddyAffiliation unknown1
B. JyothiKoneru Lakshmaiah Education Foundation1
N. Sumana KeerthiAffiliation unknown1
M. SharanyaAffiliation unknown1
CH. SrinivasAffiliation unknown1
K. ShravaniAffiliation unknown1
V. Sanjeeva RaoAffiliation unknown1
Teerdala RakeshAffiliation unknown1
Nittala RamchandraAffiliation unknown1
Devarakonda MahidharAffiliation unknown1
Burthi Loveswara RaoAffiliation unknown1
C. H. Rami ReddyAffiliation unknown1
Rakesh TeerdalaAffiliation unknown1
Kambhampati Venkata Govardhan RaoAffiliation unknown1
T. Vijay MuniAffiliation unknown1
CH. Venkata AmarnadhAffiliation unknown1
T. Anuradha DeviAffiliation unknown1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) http://section.iaesonline.com/index.php/IJEEI/oai, first harvested 8 Nov 2026, last seen 8 Nov 2026.
Original metadata (oai_dc) 
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/  http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
	<dc:title xml:lang="en">Rasa-Powered Conversational AI Framework for Intelligent Electric Vehicle Trip Planning and Energy Management</dc:title>
	<dc:creator xml:lang="en">T, Phanendra</dc:creator>
	<dc:creator xml:lang="en">G, Swapna</dc:creator>
	<dc:creator xml:lang="en">M, Vishnuvardhan</dc:creator>
	<dc:creator xml:lang="en">Rao, K V Govardhan</dc:creator>
	<dc:creator xml:lang="en">Rakesh, T</dc:creator>
	<dc:creator xml:lang="en">Kumar, M Kiran</dc:creator>
	<dc:subject xml:lang="en">Battery Management System</dc:subject>
	<dc:subject xml:lang="en">Electric Vehicle (EV)</dc:subject>
	<dc:subject xml:lang="en">Geo-Optimization</dc:subject>
	<dc:subject xml:lang="en">Grid Stability</dc:subject>
	<dc:subject xml:lang="en">Rasa NLU</dc:subject>
	<dc:subject xml:lang="en">State of Charge (SOC)</dc:subject>
	<dc:description xml:lang="en">The rapid growth of Electric Vehicles (EVs) calls for intelligent solutions to optimize grid stability and enhance user experience. This paper proposes a geo-optimized, user-centric EV management system integrating open-source geospatial tools with Rasa-based Natural Language Understanding (NLU). Through an interactive conversational interface, EV owners receive real-time trip planning recommendations based on parameters such as State of Charge (SoC), charging point availability, and route efficiency. The system utilizes APIs for real-time geolocation, charging station data, and Battery Management System (BMS) insights to determine optimal charging locations, durations, and trip costs. Extensive testing demonstrates improved energy management and route planning efficiency, highlighting the system’s potential for smart and sustainable EV infrastructure development.</dc:description>
	<dc:publisher xml:lang="en">IAES Indonesian Section</dc:publisher>
	<dc:date>2025-12-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://section.iaesonline.com/index.php/IJEEI/article/view/6553</dc:identifier>
	<dc:identifier>10.52549/ijeei.v13i4.6553</dc:identifier>
	<dc:source xml:lang="en">Indonesian Journal of Electrical Engineering and Informatics (IJEEI); Vol. 13 No. 4: December 2025; 911-922</dc:source>
	<dc:source>2089-3272</dc:source>
	<dc:source>2089-3272</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://section.iaesonline.com/index.php/IJEEI/article/view/6553/1039</dc:relation>
</oai_dc:dc>