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In this paper, we introduce, implement, and assess a framework for jointly optimizing the pricing policy and the charging schedule of electric vehicles (EVs) by learning and shaping human behavior with pricing. The proposed methodology uses time-based pricing to incentivize user behavior at charging stations towards actions that achieve the station operator's objectives. The optimization framework incorporates endogenous human behaviors by explicitly accounting for the willingness to delay charging, as well as the plug-in duration of each session, as a function of the hourly prices. The...

The increasingly popular electric vehicles (EVs) are changing the control paradigm of the power grid due to their uncoordinated charging behaviors. However, if well coordinated, smart homes, workplaces, and other locations that support EV charging could provide the grid with the urgently required flexibility via virtual power plants (VPP). In this paper, we develop the EV charging schedule model by capturing the unwillingness of EV drivers to alter their initial charging behaviors, referred to as the discomfort function. Predictability and the value of charging time, which represent the...

Charging infrastructure availability is a major concern for plug-in electric vehicle users. Nowadays, the limited public chargers are commonly occupied by vehicles which have already been fully charged. Such phenomenon, known as overstay, hinders other vehicles’ accessibility to charging resources. In this paper, we analyze a charging facility innovation to tackle the challenge of overstay, leveraging the idea of Robo-chargers - automated chargers that can rotate in a charging station and proactively plug or unplug plug-in electric vehicles. We formalize an operation model for stations...

Lithium iron phosphate (LFP) batteries are ideal for electrification of off-road heavy-duty vehicles with less concerns on the system weight. However, the limited battery life aggravated by the long working hours is a primary concern for some of-road applications such as construction equipment. Temperature is one of the main influencing factors in battery aging. Therefore, accurate prediction of temperature dynamics with fast lumped parameter models is essential and can be used for long-term analysis. This paper introduces a thermal model for pack of cells, with each cell represented by...