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Highlights• A fuzzy logic model for modeling regenerative braking systems is presented.• Model output is the ratio of regenerative braking force to the total braking force.• Model can be adapted to be used in traffic simulators like the SUMO simulator.• Real data was gathered from short and long-distance field tests with a Nissan LEAF.• Results were compared with real-world data obtained with a Nissan LEAF in road tests. AbstractR2Q3 This paper presents a fuzzy logic model of regenerative braking (FLmRB) for modeling EVs' regenerative braking systems (RBS). The model has the vehicle's acceleration and jerk, and the road inclination as input variables, and the output of the FLmRB is the regeneration factor, i.e. the ratio of regenerative braking force to total braking force. The regeneration factor expresses the percentage of energy recovered to the battery from braking. The purpose of the FLmRB development is to create realistic EV models using as least as possible manufacturers intellectual property data, and avoiding the use of EV on-board sensors. To tune the model, real data was gathered from short and long-distance field tests with a Nissan LEAF and compared with two types of simulations, one using the proposed FLmRB, and the other considering that all the braking force/energy is converted to electric current and returned back to charge the battery (100% regeneration). The results show that the FLmRB can successfully infer the regenerative braking factor from the measured EV acceleration and jerk, and road inclination, without any knowledge about the EV brake control strategy.

The 5G infrastructure initiative in Europe 1 has agreed a number of challenging key performance indicators (KPIs) to significantly enhance the user experience and support a number of use cases with very demanding requirements on the network infrastructure. At the same time there is high pressure on the reduction of the operational expenditure (OPEX). A contribution to meeting the KPIs and to reduce OPEX is to evolve the management of the network into a fully autonomic and intelligent framework. Based on advanced technologies, such as Software-Defined Networking (SDN) and Network Function Virtualization (NFV), the EU H2020 project SELFNET (https://selfnet-5g.eu/) is proposing an advanced network management framework to achieve these objectives.