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C-DAX is funded by the European Union's Seventh
Framework Programme (FP7-ICT-2011-8) under
grant agreement n° 318708
A Publish/Subscribe Communication
Framework for Managing Electric
Vehicle Charging
Dr Yue Cao,
University of Surrey
IEEE ICCVE 2014
3-7 Nov 2014
Outline
Research Overview and Motivation
Introduction on Our Proposal
Research Analysis and Method
Results Evaluation and Observations
Conclusion
Research Overview
Majority of works on Electric Vehicle (EV) charging management mainly consider static scenario
• Schedule EVs charging while they have been parking at home/charging station (when/whether to charge)
Home based charging scenario
Smart charging scenario
A few works consider EV charging management under mobile scenario
• EVs know where they should travel for charging, while they are on-the-move (where to charge)
Research Motivation on Communication Side for
On-the-Move EV Charging
Cellular network communication
• Point-to-point communication (need to know IP addresses of end users)
• Expensive even with wider radio coverage range
• Unnecessary to have ubiquitous radio coverage for on-the-move EV charging
CS-selection on where to charge is not always required
Publish/Subscribe (P/S) communication with Road Side Unit (RSU)
• Scalability
Decouple communication in space – do not need to know IP addresses of publishers and subscribers
Decouple communication in time – be tolerant to intermittent communication in VANETs, by appropriately deploying RSUs
• Reduce bandwidth usage – cost efficiency
Introduction of On-the-Move EV Charging
EVs generate charging requests while they are on-the-move during journeys
Application scenarios for on-the-move EV charging management
• Centralized decision-making (adopted by previous works)
Decision made by the global aggregator – where to charge
Ubiquitous communication – realtime information
High privacy sensitivity – EV status information (e.g., ID, location) will be released when sending charging request to aggregator
• Fully distributed decision-making (our proposed)
Decision made by individual EVs – where to charge
Opportunistically accessed communication – historical information
Low privacy sensitivity – no need to release EV status information
Network Entities
Electric Vehicle (EV): Each EV is with a Status Of Charge (SOC). Ifthe ratio between its current energy and maximum energy isbelow the value of SOC, the EV will need to request for acharging service by a CS. Here, EV is as subscriber.
Charging Station (CS): Each CS is deployed at a certain locationfor energy transaction. Here, CS is as publisher.
Road Side Unit (RSU): The deployed RSU behaves as anintermediate entity for bridging the information flow exchangebetween EVs on the road and the grid infrastructure, throughwireless communications.
Overview of Distributed Scenario
Each CS periodically publishes its condition information (e.g.demand load, EV queuing time) towards EVs through their nearbyRSUs.
Upon passing through each RSU, EVs will record this CS condition information via RSU.
• Push mode: An EV will opportunistically receive the CS publication, only when there is a CS update published while the EV is within an RSU radio coverage
• Pull mode: RSU can cache historically published CS update so that as long as an EV passes through an RSU radio coverage, it can fetch the latest update
An EV reaches its threshold in relation to SOC, starts to select the best CS using its locally recorded information.
• EV travels towards its selected CS for charging
Push mode vs. Pull mode
RSU
Published
data
RSU RSU
Published
data
RSU
Push Mode:
Periodically published data instantly advertised
to EVs in RSU coverage
Pull Mode:
Periodically published data cached at
RSU, and EVs fetch latest cached
data by sending queries
Analysis on Probability For EV to Obtain
Information From RSU
Push Mode
Pull Mode
Given 2R<S (radio range of adjacent RSUs are not overlapping)and R=L, Pull Mode achieves a higher possibility to obtaininformation, than Push Mode.
Assumption
EV passes through all RSUs evenly deployed
on straight road
Notations
V: Constant EV Speed
R: RSU Transmission Range
L: EV Transmission Range
S: Distance Between Adjacent RSUs
F: Distance From Starting Point
N: Number of RSUs
T: CS Publication Interval
𝑷𝒑𝒖𝒔𝒉 = 𝟏 − (𝟏 −𝑭 + 𝑹
𝑽 ∗ 𝑻){𝟏 − [(
𝟐𝑹
𝑺)(𝟐𝑹
𝑽 ∗ 𝑻)]}(𝑵−𝟏)
𝑷𝒑𝒖𝒍𝒍 = 𝟏 −
𝒊=𝟏
𝑵
{𝟏 − [𝒊 − 𝟏 𝑺 + 𝑭 + 𝑳
𝑽 ∗ 𝑻]}
Simulation Validation
Both Modes Benefit From Slow V
Push Mode Benefits From Large R
Push Mode Benefits From Small S
Pull Mode Benefits From Large S
Both Modes Benefit From Frequent T
Pull Mode Benefits From Large L
Calculation of Queuing Time
Queuing Time = Minimum charging time of those under charging + Aggregated value of those waiting for charging
The CS at which there is a large number of EVs parking will beestimated with a long queuing time, in particular that applyingmore charging slots contributes to a short queuing time.
Performance Evaluation
CSs and RSUs are connected via wired line
Each CS is connected to all RSUs
Parameter Value
Number of EVs 100
Number of CSs 5
Number of RSUs 7
EV Moving Speed 5-10 m/s
Radio Range of RSU 300m
Radio Range of EV 300m
CS Update Interval 100s
Status of Charge 60%
EV Initial Energy 30KWh
Maximum EV Moving Distance
161KM
CS Initial Energy 3000 KWh
CS Charging Power 62KW
Results
Observations1: Performance given frequent publication isclose to that under centralized manner.
2: Frequent publication improves informationfreshness.
3: Waiting time for charging, utilization of CSsbenefit from a good information freshness .
Ideal Case: Decision making in centralisedmanner, via realtime CS queuing time
Push/Pull Mode: Decision making indistributed manner, via historical CS queuingtime
Conclusion and Future Work
Present a Publish/Subscribe communication framework for CS-selection decision making at EV side.• Low privacy sensitivity
• Moderate charging performance given carefully set publication interval
• Cost-efficiency – no need for ubiquitous communication
In future, the remote reservation service will be integrated.• EVs report their charging reservation for selected CSs, including their
arrival time at selected CSs, and how long their charging will be
• CS-selection decision to find the CS with the minimum expected waitingtime (considering local queuing EVs and those making reservation)
• EVs charging is coordinated by considering CSs condition in a near future
Question?