Electric car (electric mobility) is one of the major challenges of our time both for the reduced environmental impact that guarantees both for the implementation of a network structure for the optimal management of the various aspects related to mobility in a Smart City. Integration with the recharging infrastructure is in particular one of the most crucial success factors as is the key element to ensure reliability and to optimal management in the charging process.
algoWatt, through its companies, has the expertise and has developed experiences and accomplishments that address the issues raised from the electric cars, integrating their management into the charging network and into the broader context of urban mobility management.
Examples are :
Charging networks
algoWatt has participated in the development of the Italian charging networks management systems, contributing to their design and development.
Electric vehicles fleets
algoWatt Fleet management systems are available in specialized version for the management of electric cars. This systems can manage cars charging, charging stations occupation times, range and trip planning.
Autonomy Optimization
algoWatt has developed tools for vehicle autonomy optimized management, with the goal to manage charging according to the needs of current trip (Ecogem, Emerld projects). The charging needs are planned together with route planning, made prior to departure or during the journey. The choice of the route takes into account the need to recharge and bookings of charging stations are managed, in order to meet in a reliable way the needs of the vehicle.
Customized information systems for electric vehicles users
Another well know product from AlgoWatt is the management of the transport system, both public and private, user information system. One of the features is the ability to manage information specifically dedicated to electric vehicles users, such as the availability of free charging stations, trip planning as a function of the availability of charging stations, the estimate of autonomy according to different traffic scenarios, location, weather conditions and optimal methods of use of the vehicle, sending dedicated informations and warnings.