Energy Recovery Assessment on Electric Bicycle Powertrain

The scientific community has widely recognized that pollution has reached a critical level and urgent action is needed to address this phenomenon. Exhaust emissions from conventionally fueled transportation systems are one of the major contributors to air pollution. To mitigate this problem, European Parliament decided to ban the sale of such vehicles by the year 2035. One potential solution to reduce pollution is the use of electric vehicles, including electric micro-mobility such as e-bikes, which have become increasingly popular in large cities due to their ability to reduce air pollution, traffic congestion, and parking problems, as well as offering a more sustainable mode of transportation. However, e-bikes still face limitations in terms of battery size, cost, and range. Following an initial examination of the e-bikes market and possible configurations, this thesis aims to investigate the potential and limitations of an e-bike equipped with a parallel powertrain and a rear hub-mounted Permanent Magnet Synchronous Motor (PMSM). Emphasis is placed on optimizing the control of the PMSM incorporating regenerative braking: using the same PMSM as a generator, the vehicle is braked and energy, that would otherwise be dissipated during mechanical braking, is recovered. This regenerative braking technique can increase the battery life on a single run. A model of the electromechanical system is developed, and simulations are performed using driving cycles obtained from experimental tests. The simulation results are then validated with experimental data. Finally, the thesis explores possibilities for future developments, particularly the development of energy management system. Studies about the efficiency of the human body during cycling are analyzed to develop algorithms for the management of the power flow, accounting not only for the optimal operating points of the electromechanical apparatus but also on the optimal operating points of the cyclist. Hence the goal is to optimize the overall efficiency of the system.