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. 2022 Apr 4;12(1):5588.
doi: 10.1038/s41598-022-08942-2.

Addressing the range anxiety of battery electric vehicles with charging en route

Prabuddha Chakraborty  1 , Robert Parker  2 , Tamzidul Hoque  3 , Jonathan Cruz  2 , Lili Du  4 , Shuo Wang  2 , Swarup Bhunia  2
Affiliations

Addressing the range anxiety of battery electric vehicles with charging en route

Prabuddha Chakraborty et al. Sci Rep. .

Abstract

Battery electric vehicles (BEVs) have emerged as a promising alternative to traditional internal combustion engine (ICE) vehicles due to benefits in improved fuel economy, lower operating cost, and reduced emission. BEVs use electric motors rather than fossil fuels for propulsion and typically store electric energy in lithium-ion cells. With rising concerns over fossil fuel depletion and the impact of ICE vehicles on the climate, electric mobility is widely considered as the future of sustainable transportation. BEVs promise to drastically reduce greenhouse gas emissions as a result of the transportation sector. However, mass adoption of BEVs faces major barriers due to consumer worries over several important battery-related issues, such as limited range, long charging time, lack of charging stations, and high initial cost. Existing solutions to overcome these barriers, such as building more charging stations, increasing battery capacity, and stationary vehicle-to-vehicle (V2V) charging, often suffer from prohibitive investment costs, incompatibility to existing BEVs, or long travel delays. In this paper, we propose Peer-to-Peer Car Charging (P2C2), a scalable approach for charging BEVs that alleviates the need for elaborate charging infrastructure. The central idea is to enable BEVs to share charge among each other while in motion through coordination with a cloud-based control system. To re-vitalize a BEV fleet, which is continuously in motion, we introduce Mobile Charging Stations (MoCS), which are high-battery-capacity vehicles used to replenish the overall charge in a vehicle network. Unlike existing V2V charging solutions, the charge sharing in P2C2 takes place while the BEVs are in-motion, which aims at minimizing travel time loss. To reduce BEV-to-BEV contact time without increasing manufacturing costs, we propose to use multiple batteries of varying sizes and charge transfer rates. The faster but smaller batteries are used for charge transfer between vehicles, while the slower but larger ones are used for prolonged charge storage. We have designed the overall P2C2 framework and formalized the decision-making process of the cloud-based control system. We have evaluated the effectiveness of P2C2 using a well-characterized simulation platform and observed dramatic improvement in BEV mobility. Additionally, through statistical analysis, we show that a significant reduction in carbon emission is also possible if MoCS can be powered by renewable energy sources.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Description of figures from left to right. (a) Growth of global BEV sales. (b) Problems preventing BEV growth. (c) Single charge range and battery charging time of high-end BEVs.
Figure 2
Figure 2
Description of figures from left to right. (a) P2C2 enabled charge sharing among BEVs and MoCS-based charge distribution for charging on-the-go. (b) A MoCS leader escorting/recharging a BEV platoon.
Figure 3
Figure 3
(a) In a P2C2 framework, BEVs and MoCS interact with each other and a control system for information/instruction sharing. The control system located in the cloud facilitates BEV-to-BEV charge sharing and optimal MoCS insertion. (b) The paired BEVs are being guided by the control system to move closer and share charge. (c) Paired BEVs speed lock and share charge on-the-go.
Figure 4
Figure 4
Description of figures from left to right. (a) The system-level view of the P2C2 framework shows the data and control flow between different entities. (b) With a two-level battery architecture, the fast (but smaller) battery can be used for BEV-to-BEV charge transfer and once detached, the smaller battery can recharge the slower-main battery.
Figure 5
Figure 5
Description of figures from left to right. (a) The percentage of halt induced charging time reduction in different traffic scenarios. (b) The charge distribution map maintained by the cloud application at a particular time instance.
Figure 6
Figure 6
Change of battery charge levels over time for sampled BEVs(red) and MoCS(blue) in the network.
Figure 7
Figure 7
(a) The percentage of BEV halts reduces as the MoCS-to-BEV charge transfer rate increases. (b) The percentage of halt increases as we decrease the battery capacity. The halt percentage is less with more MoCS in the system. (c) The percentage of BEV halts reduces as the limit on the percentage of MoCS in the network is increased.
Figure 8
Figure 8
Mobility of vehicular networks for different battery sizes and provider availability rate. Trad refers to a system without P2C2 and a monolithic battery. P2C2 refers to a system with a monolithic battery and peer-to-peer on-the-go charging. ML refers to a system with both peer-to-peer on-the-go charging and BEVs with multi-level battery. We observe that multi-level battery systems offer higher mobility at lower combined battery sizes.
Figure 9
Figure 9
Mobility of BEV networks for different battery sizes and battery charge transfer rate. Even at a higher charge transfer rate, Trad/No-P2C2 system suffers from low mobility while ML battery systems perform well even at low rates.
Figure 10
Figure 10
(a) Potential carbon footprint reduction during the operation lifecycle of a BEV if MoCS hubs are powered by solar. (b) Carbon footprint reduction considering emissions from manufacturing and battery production. (c) Proposed peer-to-peer wired charging scheme for moving vehicles.
Figure 11
Figure 11
Proposed interleaved, high power, scalable, and bidirectional on-board Buck/Boost DC/DC converters for peer-to-peer BEV charging.
Figure 12
Figure 12
Proposed strategy for fast charging of Lithium-Ion batteries: (a) Lithium-ion battery model, (b) single-pulse charging current technique to derive the internal resistance and polarization parameters of lithium-ion battery, and (c) charging speed comparison between conventional CC–CV fast charging technique and the proposed CC–CV fast charging with internal resistance and polarization parameter compensation.
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