TY - GEN
T1 - Applications of AI-Algorithms for Optimizing the Range and Minimizing the Risk of Electric Vehicles
AU - van Haentjens, Lara Sophie
AU - Torrubiano, Ruben Ruiz
AU - Reiner, Michael
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024/9
Y1 - 2024/9
N2 - Climate change and the associated effects on the environment are steadily increasing the need for alternative solutions, whether in mobility or in the economy. CO2 is the main cause of the greenhouse effect, which is emitted by the transport sector. These emissions are a major contributor to global warming and increase the risk of extreme weather events, the rise of marine play and other environmental impacts. Gases emitted today are far above 1990 levels, with an upward trend of up to a third by 2050. One solution to curb greenhouse gases and slow global warming is the use of battery-powered electric vehicles. Apart from the fact that electric vehicles are emission-free, the tax savings, for example, as well as the charging infrastructure are becoming increasingly attractive for the population. In the course of this, artificial intelligence plays an essential role and shapes everyone’s life more and more every day. The question of how vehicles can be made safer for occupants and external road users arises again and again. Artificial intelligence, with its multitude of variants and possibilities, is a ray of hope for making traffic safer in general. This paper is not only intended to show the advantages of electromobility in connection with artificial intelligence. A key factor for the end user is the range of these electric vehicles. The aim is to show how range can be optimized and where we currently stand in the electric car industry.
AB - Climate change and the associated effects on the environment are steadily increasing the need for alternative solutions, whether in mobility or in the economy. CO2 is the main cause of the greenhouse effect, which is emitted by the transport sector. These emissions are a major contributor to global warming and increase the risk of extreme weather events, the rise of marine play and other environmental impacts. Gases emitted today are far above 1990 levels, with an upward trend of up to a third by 2050. One solution to curb greenhouse gases and slow global warming is the use of battery-powered electric vehicles. Apart from the fact that electric vehicles are emission-free, the tax savings, for example, as well as the charging infrastructure are becoming increasingly attractive for the population. In the course of this, artificial intelligence plays an essential role and shapes everyone’s life more and more every day. The question of how vehicles can be made safer for occupants and external road users arises again and again. Artificial intelligence, with its multitude of variants and possibilities, is a ray of hope for making traffic safer in general. This paper is not only intended to show the advantages of electromobility in connection with artificial intelligence. A key factor for the end user is the range of these electric vehicles. The aim is to show how range can be optimized and where we currently stand in the electric car industry.
KW - artificial intelligence
KW - electromobility
KW - range optimization
KW - risk minimization
KW - Artificial intelligence
KW - Electric vehicles
UR - http://www.scopus.com/inward/record.url?scp=85204534979&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-71142-8_4
DO - 10.1007/978-3-031-71142-8_4
M3 - Conference contribution
AN - SCOPUS:85204534979
SN - 9783031711411
T3 - Communications in Computer and Information Science
SP - 51
EP - 61
BT - Systems, Software and Services Process Improvement - 31st European Conference, EuroSPI 2024, Proceedings
A2 - Yilmaz, Murat
A2 - Clarke, Paul
A2 - Riel, Andreas
A2 - Messnarz, Richard
A2 - Greiner, Christian
A2 - Peisl, Thomas
PB - Springer Science and Business Media Deutschland GmbH
T2 - 31st European Conference on Systems, Software and Services Process Improvement, EuroSPI 2024
Y2 - 4 September 2024 through 6 September 2024
ER -