In the past, the diffusion of electric vehicles (EVs) has been hindered by energy storage limits. In fact, these are the reason for the limited EV range and the consequent range anxiety of their drivers. Thanks to constant improvements in storage system technologies over the years, in terms of both energy and power density, lithium-ion batteries (LiBs) now guarantee vehicle ranges higher than 150 km for small vehicles. Another important improvement has been achieved by the hybridisation of LiBs with other storage technologies such as electric double-layer capacitors or lithium-ion capacitors. By adding an additional storage unit (ASU) to the EV battery system, the overall efficiency increases, with a consequent gain in the vehicle's expected range. In a previous paper, an optimal sizing procedure was proposed, through which it is possible to calculate the optimal ASU mass that maximises the EV range for a given vehicle, ambient conditions, and driving cycle, which was considered to be known a priori. In the present work, a real-time implementation of the control strategy on which the optimal sizing procedure was based is proposed and analysed using the results of simulation tests.
Control strategy to improve EV range by exploiting hybrid storage units
Barcellona S.;De Simone D.;Piegari L.
2019-01-01
Abstract
In the past, the diffusion of electric vehicles (EVs) has been hindered by energy storage limits. In fact, these are the reason for the limited EV range and the consequent range anxiety of their drivers. Thanks to constant improvements in storage system technologies over the years, in terms of both energy and power density, lithium-ion batteries (LiBs) now guarantee vehicle ranges higher than 150 km for small vehicles. Another important improvement has been achieved by the hybridisation of LiBs with other storage technologies such as electric double-layer capacitors or lithium-ion capacitors. By adding an additional storage unit (ASU) to the EV battery system, the overall efficiency increases, with a consequent gain in the vehicle's expected range. In a previous paper, an optimal sizing procedure was proposed, through which it is possible to calculate the optimal ASU mass that maximises the EV range for a given vehicle, ambient conditions, and driving cycle, which was considered to be known a priori. In the present work, a real-time implementation of the control strategy on which the optimal sizing procedure was based is proposed and analysed using the results of simulation tests.File | Dimensione | Formato | |
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