Detachable Electric Motor Design and Data Acquisition on Smart

Wheelchair System

Laurentius Kuncoro Probo Saputra

, Yuan Lukito

and Winta Adhitia Guspara

Informatics, Universitas Kristen Duta Wacana, Yogyakarta, Indonesia

Product Design, Universitas Kristen Duta Wacana, Yogyakarta, Indonesia

Keywords:

Detachable Electric Motor, Data Acquisition, Smart Wheelchair System.

Abstract:

Mobility for people with disabilities needs to be considered to increase their participation in activities. Hence,

every action taken can be more productive. Electric vehicles are currently a major focus of development. The

application of electric motors as propulsion in wheelchairs is highly beneﬁcial for people with disabilities, as it

enhances their mobility during activities. However, the use of electric motor propulsion in wheelchairs is a new

and interesting development, and creating a detachable electric motor propulsion device that can be used by

people who use wheelchairs is worth exploring. This study aims to examine the experience of wheelchair users

using an additional electric motor drive in their wheelchairs. Android applications for sensor data acquisition

are developed, and sensor data is transmitted from the wheelchair control system to the Android application

using Bluetooth communication. The study collects sensor data related to the use of electric motors to assess

their capabilities and responses when using this electric motor propulsion device.

1 INTRODUCTION

The Presidential Regulation of the Republic of In-

donesia Number 55 of 2019, which concerns the Ac-

celeration of the Battery Electric Vehicle Program for

Road Transportation, has opened up new opportuni-

ties for mobility and accessibility for persons with

disabilities who use wheelchairs. There are many ef-

forts that can be made to address the basic needs of

persons with disabilities in terms of mobility devices,

such as a detachable electric drive for a wheelchair.

The current advancements in battery technology have

enabled the development of higher-density batteries

that can achieve performance optimization. These

slim, lightweight, and fast-charging batteries with

sufﬁcient storage capacity are a major step toward

saving the power supply required for mobility. As the

number of electric vehicles increases, battery charg-

ing stations must be able to charge batteries quickly

(Tu et al., 2019). The combination of battery technol-

ogy and the Internet of Things (IoT) has the potential

to revolutionize the design of intelligent wheelchairs

for users. The IoT provides performance optimization

for electronic systems, information systems, and con-

trol systems to allow users to have complete control

of their electric vehicles.

Micro-mobility, also known as ”short movement,”

is an essential component of urban transportation and

occupies an important part of a city’s blueprint or ur-

ban space. The right type of vehicle with the appropri-

ate ”size and adaptation,” particularly for wheelchair

mobility on city roads, is critical and closely related

to the area traveled, energy consumption, and the type

of fuel used. Furthermore, the application of elec-

tric vehicle (EV) technology in wheelchair mobil-

ity supports the 10th Sustainable Development Goal

(SDGs) program, especially with respect to provid-

ing wheelchair users with independence and empow-

erment to access their needs, including those outside

their homes. According to data from the World Health

Organization (WHO), 5% to 15% of 70 million peo-

ple with disabilities must use wheelchairs to carry

out their daily activities (Shabibi and Kesavan, 2021).

This effort also collaborates with United Cerebral

Palsy Wheels for Humanity (UCP Wheels), which, in

2018, distributed 839 wheelchairs to its partners.

Currently, not many wheelchair users with disabil-

ities make use of electric motors to assist with their

daily activities. The objective of this study is to de-

velop a data acquisition application that will monitor

the movement of electric motors used by wheelchair

users. Furthermore, this data will be used for ana-

lyzing the experiences of individuals who use electric

motors in conjunction with their wheelchairs.

192

Saputra, L., Lukito, Y. and Guspara, W.

Detachable Electric Motor Design and Data Acquisition on Smart Wheelchair System.

DOI: 10.5220/0012446700003848

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 3rd International Conference on Advanced Information Scientiﬁc Development (ICAISD 2023), pages 192-197

ISBN: 978-989-758-678-1

Figure 1: Wheelchair Electric Drive System Design Chart.

2 LITERATURE REVIEW

2.1 Electrice Wheelchair

Wheelchairs, traditionally viewed as a mode of trans-

portation for individuals with physical disabilities,

have undergone signiﬁcant developments in the area

of electrical controls, speciﬁcally those connected to

the digital world or the Internet of Things (IoT). The

IoT-based control concept is a new paradigm in the

world of information technology, where all devices,

such as sensors, actuators, and various types of in-

dicator components, controls, and charging systems,

can be interconnected through the internet network.

Embedded systems and sensors are becoming easier

to ﬁnd, and their low cost and small size make them

well-suited for developing detachable electric drive

systems for wheelchairs that are IoT-based (Urooj

et al., 2021; Yao et al., 2015; Desai et al., 2017; Harris

et al., 2020; Parikh et al., 2007). This development is

particularly beneﬁcial for wheelchair users from dif-

ferent backgrounds. While manual wheelchairs can

only be used by individuals with physical disabilities

from the waist down, turning manual wheelchairs into

smart wheelchairs with the latest technology can pro-

vide mobility for a wider range of users. The ease

of control and navigation in smart wheelchairs, in-

cluding touch screen management, shaking or nod-

ding the head on a pad or joystick, voice commands,

and eye commands using an eye tracker, can provide

an opportunity for individuals with Alzheimer’s dis-

ease, cerebral palsy, and the elderly to have the ability

to move independently and safely (Matsumotot et al.,

2001; Simpson et al., 2002; Montesano et al., 2010;

Tomari et al., 2012; Wanluk et al., 2016).

2.2 Wheelchairair Mobility and

Accessibility

Micro-mobility, or short-distance movement, is an

important component of a city’s urban space and

transportation infrastructure. The concept of short-

distance travel is not solely about moving from point

A to point B but also considers the speed and travel

time required to connect residential areas with other

activity spaces in the city. However, this type of

short-travel vehicle faces a challenge in dense cities

due to the difﬁculty of accelerating. The issue of

short-distance travel is also closely tied to accessibil-

ity rights and equality for wheelchair users.

One problem that arises in short-distance travel is

how wheelchair users can access other activity spaces

outside their homes, such as traditional markets, hos-

pitals, schools, and government buildings (Tomari

et al., 2012). Wheelchairs are often the only means

of transportation for wheelchair users to access the

outside world where they live. This situation affects

not only accessibility rights but also the independence

and conﬁdence of wheelchair users, particularly in de-

veloping countries (Wanluk et al., 2016; Watson and

Woods, 2005). The accessibility of these spaces is

linked to the road as a hub or intermediary area. In

many situations, slow-moving modes of transporta-

tion, such as wheelchairs on highways, may face pres-

sure from faster modes of transportation. This is be-

cause they are often viewed as causing congestion or

slowing down transportation ﬂow, as is currently the

case with e-bikes in China (Hopkins, 2015).

Figure 2: Brushless Motor DC.

Figure 3: Brushless Motor DC Dimension Speciﬁcation.

Detachable Electric Motor Design and Data Acquisition on Smart Wheelchair System

193

3 DESIGN SYSTEM

Electric wheelchair propulsion is divided into three

major parts Fig. 1, namely (1) motor, (2) battery, and

(3) controller. The electric motor, as a driving force,

has a type of motor in the form of a brushless motor

with a power source using DC electric power. This

type of brushless motor is often used as a motor in

electric bicycles and electric scooters. As a power

source, this drive system uses a LiFePO4 battery. The

control system has two systems: the motor power

distribution control system and the wheelchair con-

trol system. An electric drive is required to support

wheelchair mobility. At this design stage, the electric

drive used is a brushless motor (Figure 2). Brushless

motor DC dimension is shown in Figure 3 with the

following speciﬁcations:

• Rated current: 48V

• Power: 1000W

• Shaft length: 160MM

• Applicable models: 10-inch scooter

• Fork size: 110MM

• Outer diameter: 168MM

• Width: 40MM

• Weight: 3.2kg

• Black

• Speed: 30-65km/hour

These speciﬁcations are considered very suitable

to be implemented in wheelchairs with considerations

of weight, diameter, power, and motor speed. Mean-

while, the main power source for the motor uses a

LiFePO4 battery. Based on the engine’s speciﬁca-

tions and the calculation of the motor’s power require-

ments, it depends on the battery’s resistance to sup-

port the motor’s performance.

motor

= 1000W (1)

motor

= 48V (2)

motor

1000

= 20.8 Ampere (3)

The current obtained from the motor is 20.8 A.

This current is the maximum current that the motor

can receive. If the engine is given an excess current of

20.8 A, the motor will burn out. If the current supplied

to the engine is 20 A constantly for 1 hour, then the

calculation of the battery power that must be provided

is:

bateraiPower = current time(hour)

= 20A 1 = 20 A = 20,000 mAh

(4)

Assuming the current to be used is 75% of max-

imum current, the resulting motor speed can be cal-

culated by comparing the motor’s maximum current

and maximum speed, and the motor efﬁciency factor

is greater than 87.6%.

current

max

speed

max

(5)

15A

20A

speed

65km/h

(6)

speed =

65 x 15

(7)

speed = 48.7 km/h (8)

By applying a minimum motor efﬁciency of

87.6capacity speciﬁcations will affect battery life to

provide electrical power to the motor. The greater the

battery capacity, the longer the engine can work. In

this electric drive system, the control system compo-

nents are divided into two parts, such as: (1) motor

power speed control and (2) wheelchair controller.

3.1 Motor Power Speed Control

The given element manages the allocation of elec-

tric power from the battery to the motor. It serves a

dual function as a power inverter, converting battery-

generated electricity to be used by a brushless motor

that employs three motor poles. Acting as a bridge

between the motor and the user’s engine control sys-

tem, this component facilitates adjustments in the mo-

tor’s speed and rotational direction. It also has the ca-

pability to integrate remote controls through wireless

technology. The VESC Speed Controller type compo-

nents depicted in Fig.4will be employed in the motor

power distribution control system.

3.2 Wheelchair Controller

The mentioned part serves as an intermediary control

between components and the user, speciﬁcally accept-

ing inputs transmitted via thumb throttle. Through

this control system, the user is able to operate their

wheelchair with the assistance of wireless communi-

cation technologies like Bluetooth. An Arduino Nano

controller, displayed in Figure 5, is employed by

this component to provide communication between

the motor controller and the Android application via

Bluetooth. CAN module is used as a communication

module between Arduino Nano and the motor con-

troller.

ICAISD 2023 - International Conference on Advanced Information Scientiﬁc Development

194

Figure 4: Motor speed controller.

Figure 5: Communication and Control System.

4 RESULT

The development of control system applications and

sensor data acquisition in this study aims to obtain

data related to wheelchair movement. The data ob-

tained from the sensor is to show the movement of

the detachable electric motor, namely data on mo-

tor speed, motor rpm, battery, wheelchair detachable

coordinates (latitude and longitude), wheelchair posi-

tion direction, wheelchair usage time, and wheelchair

ID. The connectivity design between the motor con-

troller module and the android smartphone is shown

in Figure 6.

Android smartphone applications are used to add

sensor data to describe the activity and movement of

wheelchairs. Data originating from the electric mo-

tor is sent to the Android application via a Bluetooth

connection in the motor control box. The rotational

speed of the engine is controlled via the Tumb Throt-

tle, which is connected to the Motor ESC via the ADC

connection.

4.1 Electric Motor Rotation Control

System

The motor rotation control is carried out through a

Thum Throttle, which will be mounted on a detach-

able electric motorbike handlebar. The Thum Throt-

tle opening value is read by the Motor ESC (Elec-

Figure 6: Design of component interconnection and com-

munication on the motor controller and display.

tronic Speed Control), which is in charge of convert-

ing the Thum Throttle opening and then passing on

the amount of electric power in A to the motor that

the motor can rotate at a certain speed. The results of

the electric power distribution control process so that

the engine can rotate are shown in Figure 7.

Figure 7: Motor Control Test with Thumb Throttle.

4.2 Control Box Design and Battery

Placement

Design and implementation of the placement of the

control box and battery placed on the handlebar pole

of the detachable electric motor. This is done so that

the center of gravity can be more evenly distributed in

the center of the complete structure between the de-

tachable electric motor and the attached wheelchair.

This helps the electric motor to have good traction to

pull the wheelchair. The stage that still needs to be

ﬁnalized is the design of the placement of the electric

control box, which takes into account the aesthetics

of the detachable electric motor. The control box po-

sition and battery placement are presented in Figure

Detachable Electric Motor Design and Data Acquisition on Smart Wheelchair System

195

Figure 8: Realization of the box and battery position design

on a detachable electric motor.

4.3 Development of Communication

Media for Sending Sensor Data

The sensor data used in this system comes from 2

devices. The ﬁrst device is the ESC motor. The

ESC motor can provide a data sensor, such as mo-

tor speed, motor rpm, and battery capacity. The ESC

motor has several ports for communication, such as a

UART port, I2C port, and CAN port. In this research,

the implementation process to get data through one

of the provided communication ports is still being de-

veloped. The communication port using the UART

port connected to the Arduino Nano until now cannot

be used to get ESC motor sensor data. This is be-

cause there is no suitable library to access data from

the ESC motor. Another step that has been done is

to try to get data using the CAN Port. Trials using

the CAN Port are still being carried out so that the

Arduino Nano can access the data from the ESC mo-

tor. Furthermore, data from the ESC motor that the

Arduino Nano can access is sent to the Android ap-

plication via Bluetooth communication.

The android application that has been designed at

this time is able to get sensor data originating from

internal smartphones, such as GPS data in the form of

latitude and longitude points, compass, and direction

data. Android applications can also be connected to

the Arduino Nano via Bluetooth connectivity, and the

Arduino Nano can send data to the Android applica-

tion. The android application developed to display a

collection of sensor data is shown in Figure 9. Fur-

thermore, ﬁnding the appropriate communication to

send data from the ESC motor to the Arduino Nano

still needs to be done.

Figure 9: Android application that displays all sensor data

sensors.

4.4 Development of Sensor Data

Communication API

The data format between the Arduino Nano and the

Android application shows is:

[#][Speed] [; ][RPM][;][BatteryVoltage]

[;][DutyCycleT hrottle][#]

This process is carried out to determine a good

data format that can be used in the communication

process between the Arduino Nano and the Android

application. In addition to displaying data from the

motor sensor, the Android application also saves the

data in a CSV ﬁle for the purpose of analyzing the

usage of the detachable electric motor, Figure 10.

Figure 10: Data in File CSV.

5 CONCLUSIONS

The system has been built, and the Android appli-

cation is now able to communicate with the motor

controller and retrieve motor sensor data. This en-

ables wheelchair users to view the speed of their

wheelchairs and monitor the battery condition while

in use. In the future, We will examine the data that

was collected to ascertain the reaction of individu-

als who use wheelchairs when operating an electric

motor-powered wheelchair.

ACKNOWLEDGEMENTS

This paper was supported in part by the Ministry

of Education and Culture of Indonesia (Grant No.

ICAISD 2023 - International Conference on Advanced Information Scientiﬁc Development

196

211/D.01/LPPM/2022)

REFERENCES

Desai, S., Mantha, S., and Phalle, V. (2017). Advances in

smart wheelchair technology. In 2017 International

Conference on Nascent Technologies in Engineering

(ICNTE, page 1–7.

Harris, A., Francis, A., Behanan, A., Fernandez, A., Sankar,

V., and George, J. (2020). Detachable module for

semi-automating a conventional wheelchair. In Dr

uck,

H., Mathur, J., Panthalookaran, V., and Sreekumar, V.,

editors, Green Buildings and Sustainable Engineer-

ing, page 463–472. Singapore, Singapore.

Hopkins, D. (2015). Transport, mobility and the produc-

tion of urban space. Geographical Research, 0(hard-

back):303 978.

Matsumotot, Y., Ino, T., and Ogsawara, T. (2001). Devel-

opment of intelligent wheelchair system with face and

gaze based interface. In Proceedings 10th IEEE Inter-

national Workshop on Robot and Human Interactive

Communication. ROMAN 2001, page 262–267. Cat.

No.01TH8591.

Montesano, L., Diaz, M., Bhaskar, S., and Minguez, J.

(2010). Towards an intelligent wheelchair system

for users with cerebral palsy. IEEE Transactions

on Neural Systems and Rehabilitation Engineering,

18:193–202.

Parikh, S., Grassi, V., Kumar, V., and Okamoto, J. (2007).

Integrating human inputs with autonomous behaviors

on an intelligent wheelchair platform. IEEE Intelli-

gent Systems, 22:33–41.

Shabibi, M. and Kesavan, S. (2021). Iot based smart

wheelchair for disabled people. In 2021 International

Conference on System, Computation, Automation and

Networking (ICSCAN, page 1–6.

Simpson, R., Poirot, D., and Baxter, F. (2002). The hep-

haestus smart wheelchair system. IEEE Transactions

on Neural Systems and Rehabilitation Engineering,

10:118–122.

Tomari, M., Kobayashi, Y., and Kuno, Y. (2012). Develop-

ment of smart wheelchair system for a user with se-

vere motor impairment. international Symposium on

Robotics and Intelligent Sensors 2012, 41:538–546.

IRIS 2012).

Tu, S., Feng, H., and Lukic, S. (2019). Extreme fast charg-

ing of electric vehicles: A technology overview. IEEE

Trans. Transp. Electrify, 5:861–878.

Urooj, S., Alrowais, F., Teekaraman, Y., Manoharan, H.,

and Kuppusamy, R. (2021). Iot based electric vehicle

application using boosting algorithm for smart cities.

Energies, 14:10 3390 14041072.

Wanluk, N., Visitsattapongse, S., Juhong, A., and Pintavi-

rooj, C. (2016). Smart wheelchair based on eye track-

ing. In 2016 9th Biomedical Engineering Interna-

tional Conference (BMEiCON, page 1–4.

Watson, N. and Woods, B. (2005). The origins and early

developments of special/adaptive wheelchair seat-

ing,”social. History of Medicine, 18:459–474.

Yao, L., Chen, Y.-Q., and Lim, W. (2015). Internet of things

for electric vehicle: An improved decentralized charg-

ing scheme. In 2015 IEEE International Conference

on Data Science and Data Intensive Systems, page

651–658.

Detachable Electric Motor Design and Data Acquisition on Smart Wheelchair System

197