An Architecture for a Large-Scale IoT e-Mobility Solution

Marek Beránek

, George Feuerlicht

, Ondřej Kučera and Vladimír Kovář

Unicorn University, V Kapslovně 2767/2,130 00 Prague 3, Czech Republic

Keywords: e-Mobility Charging Infrastructure, IoT, Software Architecture.

Abstract: The recent rapid uptake of electric vehicles is driving demand for charging infrastructure that must support

the operation of the various stakeholders of the e-mobility ecosystem. The scale and complexity of the e-

mobility domain that involves different types IoT devices and a plethora of connectivity standards makes

developing a comprehensive solution challenging. E-mobility solutions and their integration into the wider

context of smart city standards and technologies are the subject of extensive current research and rapid

evolution, but at present there are not many comprehensive solutions that deliver the required functionality

and reliability at scale. In this paper we present the Unicorn ChargeUp e-mobility solution designed to support

the operation of e-mobility Service Providers, Charge Point Operators and Electric Vehicles drivers, and

describe the ChargeUp software architecture that support reliable and scalable operation of thousands of users

and IoT devices. We describe the underlying Unicorn Architecture and show how it supports the functional

and non-functional requirements of the ChargeUp e-mobility solution.

1 INTRODUCTION

The Global EV Outlook 2021 (Zhongming et al.,

2021) estimates that there were 10 million Electric

Vehicles (EVs) on the world’s roads at the end of

2020. Electric car registrations increased by 41% in

2020, despite the pandemic-related worldwide

downturn in car sales. According to some predictions,

there will be a corresponding increase in charging

stations reaching 14 million slow and 2.3 million fast

public charging stations by 2030. There has been a

rapid increase of publicly accessible EV charging

stations in most European countries over the last five

years and starting from 2019 a gradual increase of fast

and ultra-fast charging points. Notwithstanding this

notable expansion of EV charging networks,

inequalities persist across Europe and within

individual countries in terms of accessibility of

charging points available to users; as of 2020 most

European regions have less than 0.5 EV charging

points per 1,000 inhabitants (Falchetta & Noussan,

2021). From the perspective of power grid systems,

the introduction of electric vehicles presents many

challenges, but also some opportunities. According to

Golla et al. (Golla et al., 2021), due to the rapid

https://orcid.org/0000-0003-0491-4275

https://orcid.org/0000-0001-9333-5050

acceptance of EVs in the car market, EV charging

infrastructure is becoming a key requirement. To

travel longer distances, EV drivers must be able

locate nearby charging stations and establish their

compatibility and availability. Numerous solutions

are emerging to assist EV drivers to locate suitable

charging points: for example, IoT-based monitoring

system that assists EV drivers to plan their journey

identifying optimal charging stations or an Android

application for locating available charging points and

estimating the charging time (Kharade et al., 2020).

According to Galus et al. (Galus et al., 2019),

uncontrolled charging where EVs are regarded as

passive loads without any flexibility can lead to

problems endangering secure operation of the

electricity grid. The authors argue that the

management of electric vehicles as a distributed

resource fits well within the paradigm of smart grids.

Using direct or indirect control approaches charging

of vehicles can be managed more effectively, and

additionally EVs can be used as distributed storage

resource contributing to the stability of the grid

system by frequency regulation, peak-shaving and by

integrating fluctuating renewable resources. Solid-

state switch-mode power converters have reached a

Beránek, M., Feuerlicht, G., Ku

cera, O. and Ková

r, V.

An Architecture for a Large-Scale IoT e-Mobility Solution.

DOI: 10.5220/0011827100003467

In Proceedings of the 25th International Conference on Enterprise Information Systems (ICEIS 2023) - Volume 1, pages 733-740

ISBN: 978-989-758-648-4; ISSN: 2184-4992

 2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

733

level of maturity that allows precise regulation of

voltage levels during bidirectional power flow

operation. The paper discusses the role of aggregators

that manage large fleets of EVs and the need for a

regulatory framework that facilitates advanced modes

of operation. An overview of the technical challenges

of real-time monitoring and control of Energy Storage

Systems (ESSs) for EVs and how the IoT technology

can be utilized to address the challenges and improve

the efficiency of Battery Management Systems

(BMS) is given in (Mohammadi & Rashidzadeh,

2021). Others (Arras et al., 2020) have considered

EV charging station infrastructure from both the EV

driver (charging station user) and from the provider

(charging station operator) perspectives with the view

to optimize energy cost and the duration of charging.

The energy source is selected based on availability

and costs that vary depending on the time of the day,

weather conditions, the grid load, and the specifics of

the energy source. Energy-efficiency and optimal

energy distribution are some of the most essential

issues to address when supplying energy to EVs. In

(Ouya et al., 2017), the authors propose a new

communication protocol between EVs and charging

stations that aims to improve energy management by

extending existing protocol standards to include

information for EV drivers about energy availability

within charging stations and to facilitate Vehicle-to-

Grid (V2G) energy exchange. The paper describes a

proof-of-concept system that operates over

LoRaWAN (Long Range Wide Area Network) and

provides connectivity between EVs, charging stations

and EMS (Energy Management System),

demonstrating how the proposed system could work

using a realistic scenario. It is evident that EV

charging stations are a relatively recent addition to the

multitude of smart devices and still need to be

seamlessly integrated with the rest of smart city

infrastructure so that they can instantly react to

situations such as grid overload or fire alarms in the

vicinity of a charging station. Recent proposals to

address this issue include the application of oneM2M

standard

in combination with the OCPP (Open

Charge Point Protocol) (Devendra et al., 2021).

According to Karpenko et al. (Karpenko et al., 2018)

the lack of interoperability between the various IoT

ecosystems (smart mobility, smart buildings, smart

environment, etc.) hinders the integration between

devices in different vertical IoT domains. The authors

describe a practical example of using the O-MI/O-DF

standards (Robert et al., 2016) to achieve

https://www.onem2m.org/technical/published-specifica

tions

interoperability in the smart city context and develop

a proof-of-concept EV charging mobile application

that demonstrates the feasibility of creating

distributed bottom-up services based on open

standards that unify the smart cities ecosystem.

Another challenge is the lack of coordination of EV

charging and the common practice of charging EVs

to full battery capacity irrespective of the prevailing

grid conditions. A mobile application that supports

smart charging using IoT integration with charging

station architecture taking into account individual

user preferences was proposed and implemented

(Meisenbacher et al., 2021). Phadtare et al. argue that

the current lack of availability of charging stations

combined with the lack of suitable parking is a major

limiting factor for the acceptance of electric vehicles

(Phadtare et al., 2020). The paper reviews IoT based

smart parking solutions and compares combined

parking and charging system with separate parking

and charging system. An approach to run shared EV-

charging infrastructures in the context of commercial

real-estate facilities is described in (Gauss et al.,

2022). The paper argues that CP sharing can help to

improve the overall utilization of a charging

infrastructure and can lead to a reduction of costs

associated with EV charging equipment. Rajendran et

al. (Rajendran et al., 2021) argue that the expansion

of fast-charging networks will facilitate a sustainable

transportation revolution by offering drivers versatile

choice to charge EVs for longer journeys with state-

of-the-art charging infrastructure allowing idle

batteries or EVs to operate as distributed energy

sources.

Clearly, EV charging infrastructure is a

prerequisite for the wide adoption of EVs. Successful

implementation of EV charging infrastructure

requires a comprehensive solution for EV drivers and

CPOs (Charge Point Operators), ESPs (e-mobility

Service Providers) and other stakeholders of the e-

mobility ecosystem. While there is extensive research

in this area and several small-scale prototype

solutions have been developed, there are few large-

scale implementations that provide the required level

of scalability and reliability to support thousands of

concurrent e-mobility users. In this paper we present

the Unicorn ChargeUp e-mobility solution developed

by Unicorn (unicorn.com/en/) that supports the

operation of ESPs, CPOs and EV drivers and can

reliably scaleup to thousands of EV users, charging

stations and other types of IoT devices. In the next

section (section 2) we describe ChargeUp ESP and

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ChargeUp CPO components of the system and

discuss the non-functional requirements for their

implementation. In section 3 we describe the

ChargeUp application architecture and section 4

describes the Unicorn Architecture and its role in the

implementation of the ChargeUp solution. Section 5

are our conclusions and discussion of future work.

2 UNICORN ChargeUp

The ChargeUp system is designed to support

interactions between the various e-mobility

stakeholders (EV drivers, e-mobility service

providers, charge point operators and aggregators)

and IoT devices (charging stations, smart parking

systems, off-grid batteries), and in the future with

smart grids and energy trading systems. As illustrated

in Figure 1, The Unicorn ChargeUp system consists

of two main components: ChargeUp ESP that

supports EV drivers and ChargeUp CPO designed for

Charge Point Operators.

2.1

Charg

eUp ESP

The ChargeUp ESP application enables EV drivers to

locate a suitable charging station and to charge the EV

after a payment is made. This typically involves

browsing the map on a mobile device locating an

available CP (Charging Point), displaying the features

of the charging station, and making sure that it has a

compatible connector type. The application displays

pricing information, charging limits and the current

status of the CP. The EV driver selects a charging

plan and a payment method (Figure 2). Once the

payment is processed, the customer can start charging

the EV with the application displaying information

about the progress of charging including the

remaining charging time and the amount of supplied

energy. The application controls time and price limits

in defined intervals (e.g. every 10s) and terminates

charging when the limit is reached; the customer can

terminate charging at any time using the application.

Finally, a receipt is sent to the customer via email

(Figures 3).

2.2

Char

geUp CPO

The ChargeUp CPO application manages all relevant

charging station information including technical

information needed for communication using the

OCPP protocol standard. The application runs in a

multitenant environment in which each CPO is

assigned their own application workspace

Figure 1: Unicorn ChargeUp system.

(a collection of application objects). Access to

application objects is controlled using identities that

are derived from user roles assigned to users. Each

charging station connects to a workspace of the CPO

application that controls the station and its charging

points availability.

Figure 2: Selecting a charging station and a payment

method.

Figure 3: Monitoring the charging process.

An Architecture for a Large-Scale IoT e-Mobility Solution

735

All communication between ChargeUp CPO and the

charging station is logged to the communication log

that records the timestamp, station identifier (each

charging station has a unique code that the application

uses to identify individual stations), type of OCPP

operation, type of transaction and the error code, if an

error arises. The ChargeUp CPO application displays

a list of charging stations on a map and supports basic

administrative functions that include viewing the

detail station information and the status of each CP,

unlocking connectors, terminating the charging

process, and restarting the station. ChargeUp CPO

creates a reservation of the charging point as soon as

the selected amount is blocked on the EV user’s credit

card. The operator can generate reports that display

the total energy used, total charging time, generated

revenue and other performance indicators. There are

two types of transactions: reservation and charging.

The communication log records the start and end time

for each completed transaction and stores information

about the total power consumption and the cost of the

charging transaction. During the charging session, the

application stores information about power

consumption and provides this information to the

connected ESP to enable the ESP to monitor the

charging process. The CPO deals primarily with

wholesale customers (charging operators and

aggregators), typically organizations that operate the

ESP application for end users and offer charging

services on the CPO's stations, or subjects that

represent a group of customers (e.g. car fleet users)

and who have agreed on wholesale pricing with the

CPO. In addition to generating reports of customer

details, assigned tariffs and total power consumption

of individual charging stations, the application

displays a dashboard that shows the overall status of

the system, and supports the export of data for a

defined time period that includes daily statistics for

each charging point.

2.3 Non-Functional Requirements

The ChargeUp application is implemented in the form

of SaaS (Software as a Service) and must satisfy a

number of critical non-functional requirements.

Application availability requirement is 99.97% with

a 2-hour RTO (Recovery Time Objective). This

requirement is achieved using the Unicorn Cloud

Framework (uuCloud) that isolates failures to a

specific microservice and supports automatic fail-

over (Feuerlicht et al., 2020). The ESP application

was designed to initially support 5,000 concurrent

users and 10,000 charging transactions each day. The

CPO application supports 500 CPO providers and up

to 1,000 concurrent users (dispatchers and operators)

controlling up to 10,000 charging stations. When the

need arises, uuCloud infrastructure can scale-up to a

larger number of charging stations and users while

maintaining response times below 2 seconds for view

and edit operations. The charging station OCPP

messages are typically processed within 3 seconds

from arriving at the ChargeUp CPO endpoint with a

default timeout set at 30 seconds. The ChargeUp

system is implemented using the UAF (Unicorn

Application Framework) that ensures a high level of

security via compliance with the OWASP (Open Web

Application Security Project) ASVS (Application

Security Verification Standard) level 2. All

communication with the charging stations is handled

via SOAP/HTTPS or Secure WebSocket protocol and

all transmitted data is secured by encryption.

3 CHARGEUP APPLICATION

ARCHITECTURE

The ChargeUp implementation is based on the

microservices architecture and consists of two closely

integrated applications: ChargeUp ESP and

ChargeUp CPO with clearly defined interfaces

(Figure 4). The applications use the standard OCPP

protocol for the communication with charging

stations and the communication with other systems is

facilitated via documented interfaces that support

standard electromobility protocols (OICP and OCPI).

The system logs all events, recording event

description, error identification and timestamps

enabling operators to identify software and hardware

issues as soon as they arise. The use of the uuHi GUI

framework (described in section 4) ensures that the

end user interface is consistent across all supported

devices. Both applications consist of microservices

(independent UAF sub-applications) with well-

defined APIs (Application Programing Interfaces) to

ensure scalability and reliable operation of the

system.

ChargeUp ESP is divided into two core

microservices:

─ Main – a microservice that manages the interaction

with charging stations via ChargeUp CPO Main.

To ensure that the data and control of charging

stations is strictly separated, each provider of

charging stations has their own application

workspace that includes this microservice.

─ Portal – a microservice that supports

communication between EV drivers and the ESP

Main microservice. The portal is also responsible

─

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Figure. 4: ChargeUp application architecture.

for communicating with the payment gateway and

for micro-transaction management.

ChargeUp CPO is divided into 6 separate

microservices:

─ Main microservice that manages charging stations

and the charging process.

─ CPR microservice that translates different versions

of OCPP into a unified internal ChargeUp CPO

API.

─ Reporting microservice for the management of

reporting data and generation of reports.

─ Communication log microservice that manages the

communication log and related audit functions.

─ Gateway microservice that transforms WebSocket

communication into the standard Unicorn

Application Framework REST-like command

calls.

─ Customer & Contract management microservice

that manages customer and customer contract

information.

4 THE UNICORN

ARCHITECTURE

In this section we describe the role of the Unicorn

Architecture in the implementation of the ChargeUp

system. The implementation of the ChargeUp system

derives its functional and non-functional properties

from the underlying architecture. The Unicorn

Architecture supports a range of mobile and IoT

devices and facilitates cloud deployment of enterprise

applications utilizing standard state of the art

technology components and services that include

security and authentication services, GUI (Graphical

User Interface) components and services for the

deployment and operation of containerized

microservices. The Unicorn Architecture is based on

technology standards that implement various layers

of the architecture and provide a stable basis

for the implementation of enterprise applications.

Unicorn Architecture consists of four interrelated

frameworks:

uuHi - specification and corresponding

framework services for the development of GUI

components.

uuTi - specification and corresponding

framework services for the management of IoT

devices and various appliances that interact with

enterprise applications.

uuAppServer - specification and corresponding

framework services for the development of

containerized microservices applications.

uuCloud - specification and corresponding

framework services that support the provisioning of

elastic cloud services.

The Unicorn Architecture frameworks play a key

role in supporting the development and operation of

the ChargeUp system. The uuHi GUI components

based on the HTML5 specification (WC3, 2017),

JavaScript (JavaScript, 2017), CSS3 (Storey, 2012)

An Architecture for a Large-Scale IoT e-Mobility Solution

737

and React (React - A JavaScript library for building

user interfaces, 2017) support rapid development of

reliable and scalable cloud-based mobile applications

for a wide variety of devices, including mobile

phones, tablets, notebooks, smart TVs and desktop

computers. The uuHi framework facilitates

integration with React and other commonly used GUI

libraries. This ensures that the application screens

illustrated in Figures 2 and 3 are dynamically adjusted

to a specific display environment without the need to

customize the UI code.

The IoT uuTi framework provides integration

with charging stations from different manufacturers

via the OCPP protocol (v1.5 and v1.6) and supports a

range of operations such as restarting the charging

station, unlocking a charging point, checking for

availability of charging stations and individual

charging points, viewing the communication log, etc.

The CPO gateway acts as a translator of WebSocket

requests into HTTPS requests of the CPR

microservice. As shown on Figure 5, incoming (from

a charging station to the CPO application) WSS

requests pass through the CPO gateway and are

transformed into commands (API calls) of the CPR

service. Outgoing WSS requests (from the CPO

application to a charging station) pass through the

CPO gateway, and SOAP/HTTPS requests are sent

directly between the CPR service and the charging

station.

Figure 5: Processing of requests between a charging station

and the CPO Main microservice.

The uuCloud framework (Beranek et al., 2018)

maintains active information about all objects within

the cloud environment and automates the deployment

and operation of container-based microservices. To

ensure portability, individual microservices are

provisioned in the form of Docker containers

(Docker, 2015) and deployed to the Microsoft Azure

public cloud infrastructure, but could be deployed to

another compatible cloud platform (e.g. AWS), if the

need arises. Access to individual microservices is

controlled using identity (uuIdentity) associated with

user roles and assigned to individual users and system

commands. uuIdentity authentication is managed by

the uuOidc service that supports secure storage of

data and integrates with third-party identity providers

(e.g., Facebook, Google, etc.). The uuCloud security

model is based on a combination of Application

Profiles (collection of functions that the application

can execute) and Application Workspaces (collection

of application objects that the application can access).

Access to Application Workspaces is granted

according to identities associated with the

corresponding Application Profile. The uuCloud

framework supports multitenancy with each tenant

(typically a separate organization, e.g., a CPO)

assigned resources from a Resource Pool using the

mechanism of Resource Lease. uuCloud unit of

deployment is a node; each containerized

microservice is implemented using a node image that

contains the application code and a runtime stack that

includes all the related archives and components

needed to run the application (system tools, system

libraries, etc.). Nodes are stateless and use external

resources (e.g. MongoDB databases) for persistent

storage. Nodes are classified as synchronous or

asynchronous, depending on the behavior of the

application that the node virtualizes and are grouped

into NodeSets - sets of nodes with identical

functionality. Horizontal scalability is achieved by

creating additional instances (nodes) of containerized

microservices on demand depending on the number

of concurrent users and the volume of charging

transactions. At runtime, a gateway (uuGateway)

forwards client requests to a router that passes each

request to a load balancer. The load balancer selects a

node from a NodeSet optimizing the use of the

hardware infrastructure and at the same time

providing a failover capability by re-directing the

request to an alternative node within the NodeSet if a

particular node is unresponsive.

4.1 Infrastructure Services

In addition to the above frameworks, the Unicorn

Architecture incorporates infrastructure services that

provide common functions such as authentication and

authorization, persistence, inter-service communica-

tions and other functions that are frequently used

across different application systems. These include

the uuOidc service based on the OpenID Connect

standard (Sakimura et al., 2012), the

uuMessageBroker service for fast, reliable, secure,

and scalable event-based communication via queues,

the uuAsyncJob service that supports running ad-hoc

and scheduled jobs that improve the performance and

scalability of applications by executing CPU-

intensive application as background processes, and

the uuPaymentGateway service that supports third-

party payment gateways and integrates with various

e-shops and partner websites. Additionally, the

architecture includes multi-lingual and customization

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facilities that allow individual application

workspaces to be configured for specific needs of

different countries.

5 CONCLUSIONS

Increasing adoption of EVs in Europe and across the

world is driving demand for EV charging

infrastructure that must include reliable and scalable

enterprise applications that support the operation of

the various participants of the e-mobility ecosystem.

The scale and the complexity of the e-mobility

domain that involves various stakeholders (EV

drivers, ESPs, CPOs, aggregators, etc.), different

types IoT devices from various manufactures

(charging stations, EVs, etc.) and a plethora of

standards as well as demanding application

requirements makes developing a comprehensive

solution challenging. In this paper we have described

the Unicorn ChargeUp e-mobility solution that

supports the operation of ESPs, CPOs and EV drivers

and is currently used by organizations in the Czech

Republic and across Europe. As with most software

projects of this scale and complexity, the

implementation of ChargeUp involved some

challenges. Integrating a set of heterogenous IoT

devices (different models of charging stations from

different manufacturers) and keeping their firmware

up-to-date requires a continuous effort. Different

vendor implementations of the OCPP necessitate

extensive testing to ensure the stability of the system.

Early versions of ChargeUp were implemented on top

of our existing platform for energy-related projects

designed to process large volumes of time-series data,

but this platform proved not to be sufficiently scalable

in an environment with a large number of users, IoT

devices and a high volume of transactions.

Implementing more recent versions of ChargeUp

using the Unicorn Architecture ensures that both the

functional and non-functional requirements described

in sections 2 and 3 can be supported in the future with

growing number of users and transactions. Another

implementation challenge involved accommodating

the diverse requirements of ChargeUp CPO and

ChargeUp ESP applications that address different

end-user scenarios. While charge point operators can

be trained in the use of the application and related

documentation, users of the ESP application (EV

drivers) must be able to operate the application

without training and without the comfort of office

environment, typically using a small screen of a

mobile phone. The design of the user interface must

reflect these requirements. Currently, most charging

solutions (including ChargeUp) use charging stations

only for charging of electric vehicles. In the future,

charging solutions will become an integral

component of smart grids allowing for improved

monitoring of the energy distribution network and

optimization of energy consumption, avoiding usage

peaks by motivating users to charge their vehicles

during off-peak periods (Alyousef, 2021). Our

current efforts include extending the ChargeUp

system to include smart parking functionality and

eventually incorporating support for grid-friendly EV

charging with the ability to adjust the power demand

to reflect the real-time status of the power grid. Data

generated by the ChargeUp application will play an

important role in balancing out the conflicting

requirements of different stakeholders in an EV

ecosystem.

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