This paper proposes an energy management system (EMS) for shared electric bicycles.The objective is to guarantee electric assistance to the cyclist while avoiding discharging the battery. The basic working principle exploits the cycling efficiency gaps.The proposed multi-layered EMS is specifically tailored to a free-floating bike sharing setting. The innermost layer manages the assistance and energy harvesting with the objective of yielding an intuitive human-machine interface. The middle level modulates the level of assistance so to track a desired average battery power. This is an adaptive model-based controller designed on a control-oriented model of the cyclist and bicycle energy dynamics. A cyclist profiling mechanism enables the model adaptation. The outermost loop guarantees the long term robustness by tracking a desired battery state of charge profile.Extensive simulations and experimental tests validate this approach in terms of usability and charge sustenance, proving that the cyclist profiling is of paramount importance.
In this paper, we study a security problem for attack detection in a class of cyber-physical systems consisting of discrete computerized components interacting with continuous agents. We consider an attacker that may inject recurring signals on both the physical dynamics of the agents and the discrete interactions. We model these attacks as additive unknown inputs with appropriate input signatures and timing characteristics. Using hybrid systems modeling tools, we design a novel hybrid attack monitor and, under reasonable assumptions, show that it is able to detect the considered class of recurrent attacks. Finally, we illustrate the general hybrid attack monitor using a specific finite time convergent observer and show its effectiveness on a simplified model of a cloudconnected network of autonomous vehicles.
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