The lack of sustainable solutions to mobility and transportation is a major problem in Latin American cities and requires prompt solutions. The main issues in Latin America are the high-cost of solutions, no inclusion of renewable energies, poor energy management, the use of foreign systems not adapted to local contexts, ineffective regional legislation and politics, among others. In this paper the main technical issues concerning the implementation of a bike-sharing system using pedaling-assisted (PAS) electric bicycles for Bogota City are discussed and a solution is proposed. To solve such problems, a methodology to design a tailored solution well suited to Bogota citizen’s needs is developed. Such methodology starts with the development of an on-board-computer (OBC) in order to characterize bike-users by collecting a rider’s data in real-time. Furthermore, the proposed solution develops a low-cost middle-drive (mid-drive) propulsion system for the PAS in the electric bike using brushless-DC (BLDC) motors and by implementing a field-oriented controller (FOC). The reported bike-sharing system also includes the development and implementation of two charging-stations that enable charging the battery on the electric bikes exclusively by using photovoltaic energy. Experimental results are presented and discussed.
International audienceThis paper presents a real-time MPC-based tracking strategy for linear systems subject to time-varying constraints. The framework is quite general since time-varying constraints in the state and in the input are considered. To handle the problem, a polytopic invariant set computed offline is homogeneously dilated and contracted on-line to fit the polytopic time-varying constraints, and used as an admissible terminal set constraint to guarantee stability and convergence in the tracking task. The on-line cost of the homothetic invariant set computation is negligible and allows dealing with tracking problems for real-time applications
It is described a complete benchmark designed for testing performances of an electric vehicle in terms of consumption during the European Shell Eco-marathon race. A model of the electric vehicle built for the race is first obtained. Then, a low consumption driving strategy is derived. The tracking performances are tested on the electric Vir'Volt benchmark prototype, wherein a Model Predictive real-time Controller has been implemented. The experimental result are detailed.
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