• Energy Research

The proliferation of electric vehicles (EVs) has posed significant challenges to the existing power grid infrastructure. It thus becomes of vital importance to efficiently manage the Electro-Mobility for large demand from EVs. Due to limited cruising range of EVs, vehicles have to make frequent stops for recharging, while long charging period is one major concern under plug-in charging. We herein leverage battery swapping (BS) technology to provide an alternative charging service, which substantially reduces the charging duration (from hours down to minutes). Concerning in practice that various battery is generally not compatible with each other, we thus introduce battery heterogeneity into the swapping service, concerning the case that different types of EVs co-exist. A battery heterogeneity-based swapping service framework is then proposed. Further with reservations for swapping service enabled, the demand load can be anticipated at BS stations as a guidance to alleviate service congestion. Therefore, potential hotspots can be avoided. Results show the performance gains under the proposed scheme by comparing to other benchmarks, in terms of service waiting time, etc. In particular, the diversity of battery stock across the network can be effectively managed.

The proliferation of electric vehicles (EVs) has posed significant challenges to the existing power grid infrastructure. It thus becomes of vital importance to efficiently manage the Electro-Mobility for large demand from EVs. Due to limited cruising range of EVs, vehicles have to make frequent stops for recharging, while long charging period is one major concern under plug-in charging. We herein leverage battery swapping (BS) technology to provide an alternative charging service, which substantially reduces the charging duration (from hours down to minutes). Concerning in practice that various battery is generally not compatible with each other, we thus introduce battery heterogeneity into the swapping service, concerning the case that different types of EVs co-exist. A battery heterogeneity-based swapping service framework is then proposed. Further with reservations for swapping service enabled, the demand load can be anticipated at BS stations as a guidance to alleviate service congestion. Therefore, potential hotspots can be avoided. Results show the performance gains under the proposed scheme by comparing to other benchmarks, in terms of service waiting time, etc. In particular, the diversity of battery stock across the network can be effectively managed.

As a key enabler in the green transport system, the popularity of Electric Vehicles (EV) has attracted attention from academia and industrial communities. However, the driving range of EVs is inevitably affected by the insufficient battery volume, as such EV drivers may experience trip discomfort due to a long battery charging time (under traditional plug-in charging service). One feasible alternative to accelerate the service time to feed electricity is the battery switch technology, by cycling switchable (fully-recharged) batteries at Battery Switch Stations (BSSs) to replace the depleted batteries from incoming EVs. Along with recent advance of vehicle cooperation through emerging Information Communication Technology (ICT), in this paper we propose a Mobile Edge Computing (MEC) driven architecture to gear the intelligent battery switch service management for EVs. Here, the decision making on where to switch battery is operated by EVs in a distributed manner. Besides, the Vehicle-to-Vehicle (V2V) communication in line with public transportation bus system is applied to operate flexible information exchange between EVs and BSSs. Dedicated MEC functions are positioned for bus system to efficiently disseminate BSSs status and aggregate EVs’ reservations, concerning the massive signalling exchange cost. The Global Controller (GC) is positioned as cloud server to gather BSSs (service providers) status and EVs’ reservations (clients), and predict the service availability of BSS (e.g., whether/when a battery can be switched). We conduct performance evaluation to show the advantage of MEC system in terms of reduction of communication cost, and BSS service management scheme regarding reduction of service waiting time (e.g., how long to wait for battery switch) and increase of service satisfaction rate (e.g., how many batteries to switch for EVs).

As a key enabler in the green transport system, the popularity of Electric Vehicles (EV) has attracted attention from academia and industrial communities. However, the driving range of EVs is inevitably affected by the insufficient battery volume, as such EV drivers may experience trip discomfort due to a long battery charging time (under traditional plug-in charging service). One feasible alternative to accelerate the service time to feed electricity is the battery switch technology, by cycling switchable (fully-recharged) batteries at Battery Switch Stations (BSSs) to replace the depleted batteries from incoming EVs. Along with recent advance of vehicle cooperation through emerging Information Communication Technology (ICT), in this paper we propose a Mobile Edge Computing (MEC) driven architecture to gear the intelligent battery switch service management for EVs. Here, the decision making on where to switch battery is operated by EVs in a distributed manner. Besides, the Vehicle-to-Vehicle (V2V) communication in line with public transportation bus system is applied to operate flexible information exchange between EVs and BSSs. Dedicated MEC functions are positioned for bus system to efficiently disseminate BSSs status and aggregate EVs’ reservations, concerning the massive signalling exchange cost. The Global Controller (GC) is positioned as cloud server to gather BSSs (service providers) status and EVs’ reservations (clients), and predict the service availability of BSS (e.g., whether/when a battery can be switched). We conduct performance evaluation to show the advantage of MEC system in terms of reduction of communication cost, and BSS service management scheme regarding reduction of service waiting time (e.g., how long to wait for battery switch) and increase of service satisfaction rate (e.g., how many batteries to switch for EVs).

While previous studies focused on managing charging demand for private electric vehicles (EVs), we investigate ways of supporting the upgrade of an entire public urban electric taxi (ET) system. Concerning the coexistence of plugin charging stations (CSs) and battery swap stations (BSSs) in practice, it thus requires further efforts to design a holistic charging management especially for ETs. By jointly considering the combination of plug-in charging and battery swapping, a hybrid charging management framework is proposed in this paper. The proposed scheme is capable of guiding ETs to appropriate stations with time-varying requirements depending on how emergent the demand will be. Through the selection of battery charging/swap, the optimization goal is to reduce the trip delay of ET. Results under a Helsinki city scenario with realistic ETs and charging stations show the effectiveness of our enabling technology, in terms of minimized drivers’ trip duration, as well as charging performance gains at the ET and station sides.

While previous studies focused on managing charging demand for private electric vehicles (EVs), we investigate ways of supporting the upgrade of an entire public urban electric taxi (ET) system. Concerning the coexistence of plugin charging stations (CSs) and battery swap stations (BSSs) in practice, it thus requires further efforts to design a holistic charging management especially for ETs. By jointly considering the combination of plug-in charging and battery swapping, a hybrid charging management framework is proposed in this paper. The proposed scheme is capable of guiding ETs to appropriate stations with time-varying requirements depending on how emergent the demand will be. Through the selection of battery charging/swap, the optimization goal is to reduce the trip delay of ET. Results under a Helsinki city scenario with realistic ETs and charging stations show the effectiveness of our enabling technology, in terms of minimized drivers’ trip duration, as well as charging performance gains at the ET and station sides.