AI electromobility for Europe

Togeth­er with nine part­ners, Land­shut Uni­ver­si­ty of Applied Sci­ences is devel­op­ing a data-based con­cept to expand the charg­ing infra­struc­ture for elec­tro­mo­bil­i­ty and relieve the strain on Europe’s traf­fic and elec­tric­i­ty net­works. The Ger­man Fed­er­al Min­istry of Dig­i­tal Affairs and Trans­port is fund­ing the project with a total of almost 4.2 mil­lion euros.

The expan­sion of elec­tro­mo­bil­i­ty and the nec­es­sary charg­ing infra­struc­ture is one of the Euro­pean Union’s core objec­tives. Fast charg­ing and net­work sta­bil­i­ty are the main issues here. The con­cepts for this require com­pre­hen­sive data, on the basis of which the effects on grid sta­bil­i­ty, sus­tain­abil­i­ty and the poten­tial for opti­miza­tion can be assessed. How­ev­er, since hard­ly any stud­ies have been car­ried out on this so far, the data sit­u­a­tion is very lim­it­ed. This is where the new Open Mobil­i­ty Elec­tric Infra­struc­ture (OMEI) research project led by Land­shut Uni­ver­si­ty of Applied Sci­ences comes in.

The project team, which con­sists of a total of ten insti­tu­tions and com­pa­nies, wants to cre­ate a freely avail­able data basis for plan­ning a sus­tain­able, region­al charg­ing infra­struc­ture and eval­u­at­ing con­cepts for the intel­li­gent use of e‑vehicles. Based on this, the con­sor­tium will also devel­op opti­mal eco­log­i­cal, eco­nom­ic and tech­ni­cal solu­tions for charg­ing infra­struc­tures in the Euro­pean trans­port net­work that com­bine region­al renew­able ener­gies with sus­tain­able ener­gy stor­age. The con­sor­tium thus aims to cre­ate a data-based con­cept trans­fer­able to Europe on how elec­tro­mo­bil­i­ty can be expand­ed sus­tain­ably and eco­nom­i­cal­ly. The Ger­man Fed­er­al Min­istry of Dig­i­tal Affairs and Trans­port is fund­ing the project with a total of almost 4.2 mil­lion euros.

Strain on European transport networks

“The nec­es­sary expan­sion of elec­tric charg­ing infra­struc­ture is plac­ing an enor­mous bur­den on Euro­pean trans­port and elec­tric­i­ty net­works; to meet the pow­er demand, we need fast-charg­ing sys­tems on the main trans­port routes through­out Europe.”

- Prof. Dr. Karl-Heinz Pet­tinger, Sci­en­tif­ic Direc­tor at the Ener­gy Tech­nol­o­gy Center

Such a grid expan­sion, how­ev­er, is very resource-inten­sive, he said. There­fore, it is impor­tant to cre­ate sus­tain­able and grid-friend­ly charg­ing infra­struc­tures and to use more region­al renew­able ener­gies for this purpose.

Intelligent charging infrastructure with the help of AI

The researchers there­fore want to col­lect charg­ing, user, ener­gy and traf­fic data as a first step in order to cal­cu­late the effects of a smart charg­ing infra­struc­ture on the ener­gy tran­si­tion. To this end, the team is set­ting up demon­stra­tion facil­i­ties in two mod­el regions along a major Euro­pean arte­r­i­al road (e.g., along the A3 high­way) that com­bine a fast-charg­ing sta­tion with a hybrid ener­gy stor­age sys­tem. This would allow more region­al ener­gy to be used to charge e‑cars, with the ener­gy stor­age serv­ing as a pow­er buffer.

This would put less strain on the Euro­pean sup­ply net­work and save costs in expand­ing suprare­gion­al charg­ing infra­struc­ture. In addi­tion, the team is plan­ning a third end-user facil­i­ty that is bidi­rec­tion­al, mean­ing e‑cars can be both charged and dis­charged. “In this vehi­cle-to-home vari­ant, we want to use the poten­tial of the avail­able stor­age capac­i­ties of the sta­tion­ary vehi­cles and thus devel­op grid-based charg­ing or dis­charg­ing sce­nar­ios with the help of arti­fi­cial intel­li­gence,” Prof. Pet­tinger said. The team’s goal is to ulti­mate­ly present a holis­tic con­cept for a sus­tain­able charg­ing infra­struc­ture with the help of these two approaches.

Taking the topic into society

For exam­ple, the sci­en­tists use the col­lect­ed data to cre­ate sim­u­la­tion mod­els in order to devel­op and opti­mize loca­tion-inde­pen­dent and eco­nom­i­cal oper­at­ing strate­gies. The gen­er­at­ed data will even­tu­al­ly be made acces­si­ble via open data por­tals. In addi­tion, the con­sor­tium wants to take the top­ic into soci­ety through active cit­i­zen par­tic­i­pa­tion in order to gen­er­ate accep­tance for nec­es­sary changes. The results will there­fore be pub­lished trans­par­ent­ly in a user app.

Close cooperation of the consortium 

In order to be able to imple­ment the project as planned, the project part­ners are work­ing togeth­er in close exchange: While the bat­tery man­u­fac­tur­ers JB, FENECON as well as the charg­ing sta­tion oper­a­tor MER are respon­si­ble for the con­struc­tion and oper­a­tion of the ener­gy stor­age sys­tems and fast charg­ing sta­tions, respec­tive­ly, the TZE togeth­er with HEITEC devel­ops the sys­tem design as well as the oper­at­ing strate­gies of the charg­ing infra­struc­ture and the ener­gy stor­age sys­tems. In addi­tion, the TZE, togeth­er with the Uni­ver­si­ty of Pas­sau, is respon­si­ble for the sim­u­la­tion mod­els and tests the vehi­cle-to-home appli­ca­tions. Dr. Gerl, the sci­en­tif­ic project coor­di­na­tor for the Chair of Dis­trib­uted Infor­ma­tion Sys­tems, empha­sizes that “only with an exten­sive and sus­tain­ably avail­able data­base can it be pos­si­ble to devel­op AI-based sys­tem sim­u­la­tions and opti­miza­tions for elec­tric charg­ing infra­struc­tures in Europe. This is the focus of our subproject.”

The com­pa­ny Tech­nagon is devel­op­ing a bidi­rec­tion­al wall­box for vehi­cle-to-home appli­ca­tions with coor­di­na­tion of the tech­ni­cal require­ments. TZE, IL and Tech­nagon val­i­date and test this appli­ca­tion at the respec­tive loca­tions and test vehi­cles. Based on pow­er grid and smart meter data, pro­vid­ed by EVG Per­lesreut eG, these oper­at­ing strate­gies will be val­i­dat­ed and opti­mized for V2G appli­ca­tions. Final­ly, an oper­at­ing con­cept for vehi­cle stor­age (V2G/V2H) will be devel­oped in the consortium.

Sustainable energy supply for e‑mobility

In the end, the project should help to expand elec­tro­mo­bil­i­ty, avoid grid con­ges­tion and enable cit­i­zens to use elec­tric dri­ves in a sus­tain­able way. Prof. Kosch and Prof. Sauer togeth­er empha­size the pro­jec­t’s tech­no­log­i­cal inno­va­tion. “The data-based opti­miza­tion of the elec­tric charg­ing infra­struc­ture as well as the real­iza­tion of vehi­cle-to-home and vehi­cle-to-grid con­cepts in Bavaria is an impor­tant mile­stone for the future-capa­ble sus­tain­able mobil­i­ty sys­tem in Ger­many,” Prof. Kosch elab­o­rates. Prof. Sauer adds that “the use of AI meth­ods to increase ener­gy effi­cien­cy in vehi­cle-to-home net­work­ing has a very high poten­tial, and the project results will be very rel­e­vant for the region­al ener­gy ecosys­tem.” “It is impor­tant to us to ensure a sus­tain­able ener­gy sup­ply for elec­tric mobil­i­ty,” says Prof. Pet­tinger, “thus reduc­ing the car­bon foot­print of each e‑vehicle.”