Fabrication of an Extended Electric Bike
Muhammad Shahid1,
Muhammad Awais Hafeez1,
Muhammad Usman Khan2, Muhammad Anns3, Muhammad Abdullah4, Zohair Arif2
1Department of Mechatronics
and Control Engineering, University of Engineering and Technology Lahore, Faisalabad
Campus, Faisalabad, Pakistan
2Bioproducts Sciences and
Engineering Laboratory, Washington State University, Tri-cities, Wahington,
USA
3Faculty of Information
Technology and Electrical Engineering, University of Oulu, Oulu, Finland
4Institute of Metallurgy
and Materials Engineering, University of the Punjab, Lahore, Pakistan
|
METADATA Paper history Received: 20 February
2025 Revised: 27 June 2025 Accepted: 29 August
2025 Published online:
26 September 2025 Corresponding
author Email: drmshahid@uaf.edu.pk (Muhammad
Shahid) Keywords Hybrid electric
vehicle Urban bike Energy efficiency Fossil fuel Citation Shahid M, Hafeez
MA, Khan MU, Anns M, Abdullah M, Arif Z (2025) Fabrication of an extended
electric bike. Innovations in STEAM: Research & Education 3: 25030201.
https://doi.org/10.63793/ISRE/0026.
|
ABSTRACT Background:
The fabrication of an Extended Electric Bike (EEB) has been developed
as a practical solution for low-income communities. It aims to reduce
pollution and ensure compliance with government regulations. Surveys were
conducted to gather feedback on electric and hybrid bikes, which supported the
design process. Objective:
The objective of EEB is to create a user-friendly hybrid bike that
utilizes both fossil fuel (petrol) and batteries, providing a sustainable and
convenient mode of transportation. Methodology:
The system was
configured to utilize a petrol-powered alternator for charging onboard
batteries, which subsequently supplied power to a brushless direct current
(BLDC) motor for propulsion. Before the operation, the batteries were fully
charged to ensure continuous performance. During operation, the alternator
recharged the batteries, thereby extending usage time without the need for
external charging. In cases of battery depletion, the petrol engine served as
a backup power source. An Arduino microcontroller was employed to regulate
system functions, including real-time monitoring of battery status and
automatic switching between petrol and battery power. Results:
The fabricated
design successfully integrated petrol and battery power. The alternator-based
charging system eliminated the need for external charging, while the
Arduino-controlled unit ensured efficient power management and enabled
Internet of Things (IoT) functionality. Conclusion:
The EEB design effectively addressed transportation challenges by
offering a dual-power system that reduces pollution, supports low-income
communities, and enhances user convenience through smart control features. |
INTRODUCTION
In many developing countries,
energy resources are limited, and environmental protection is often not given
priority (Zahedi et al. 2025). Internal combustion (IC) motorcycles are
a major source of pollution, releasing carbon dioxide, carbon monoxide, sulfur
oxides, nitrogen oxides, and lead (Sugiarto et al. 2025). These
emissions create serious environmental problems. Electric motorcycles provide
an alternative by supplying power directly to the motor rather than relying on
fuel combustion. Unlike IC engines, they do not consume fuel or produce exhaust
when idling. However, electric motorcycles also have limitations. Under heavy
load, the battery drains more quickly, which reduces speed and can eventually
stop the bike. In addition, the absence of portable charging systems makes them
less practical, and without such systems, their use becomes restricted. The
concept of an extended electric bike has the potential to address these issues
by improving performance, reliability, and efficiency. At the global level,
electric vehicles are gaining attention because of both economic and
environmental concerns. Rising oil demand, increasing fuel prices, and the
effects of climate change have accelerated this shift. The transport sector is
one of the largest contributors of greenhouse gases, including CO₂ and
CH₄. In recent years, environmental awareness and the search for cleaner
energy alternatives have grown to a stage where they cannot be ignored. As a
result, electric power in transportation is expanding, reflecting the global
move toward sustainable and pollution-free mobility.
In Pakistan, the demand for fuel-efficient and environmentally friendly
motorcycles is particularly high because a large part of the population lives
in urban areas. Vehicles that combine conventional engines with electric motors
can reduce fuel use and emissions. Fossil fuel, mainly petrol, is still widely
used, but the country is not entirely dependent on it. New technologies such as
regenerative braking, where the electric motor on the wheel reduces vehicle
speed while recharging the battery, further lower the power demand (Sheu 2020;
Nosratzadehi et al. 2025).
Although
electric vehicles are more efficient than IC engine motorcycles, their higher
cost and lower speed have limited their adoption. Increasing production can
make them more affordable and attractive to users. A recent advancement is the
extended electric bike, which has strong potential to expand its access to
sustainable and pollution-free mobility. The addition of Internet of Things
(IoT) features enhances this design by allowing real-time monitoring, GPS
tracking, route information, emission detection, and advanced security systems.
These advantages demonstrate the promise of IoT-based extended electric bikes
in addressing transportation challenges (Hadayat et al. 2025).
MATERIALS AND METHODS
The
extended model of the electric bike is designed to operate on the principle of
dual-drive functionality, utilizing two independent power sources. The motor
receives energy first from a battery and subsequently from an alternator.
Battery
source
The
motor is powered by a 20Ah battery operating at 48V. Dry-cell batteries
manufactured by YUASA were employed for this purpose. The battery consists of
eight individual 12V cells connected in series as four sets of two cells. This
configuration enables the system to deliver 48V and 20A under full operating
conditions. The battery supplies power to the motor, thereby propelling the
vehicle.
Charging
methods
Two
distinct charging methods were adopted. The first is the plug-in charging
method, utilizing electricity from the grid, which is readily available.
Charging requires 4–5 hours and consumes approximately 1.5 units of electricity
to reach full capacity. When fully charged, the vehicle can travel
approximately 60 kilometers at maximum speed while carrying loads up to 250 kg.
The maximum speed achieved under these conditions is 60 km/h. Upon ignition,
the controller evaluates the charge status and displays the remaining power. If
the charge level falls below 15%, the controller automatically initiates engine
ignition. The second method is alternator-based charging. In this
configuration, the alternator derives mechanical power from the engine once it
is activated. The alternator supplies power to both the engine and the battery
while simultaneously recharging the latter.
A
boost converter was integrated to maximize charging efficiency by amplifying
the current and filtering harmonic distortions. The dynamo, coupled with the
motor, enables charging during motion. Four LED indicators reflect charging
status, with each light representing 25% capacity. Once the battery reaches
full capacity, the engine disengages automatically, and the battery assumes
exclusive operation of the motor. The tachometer is monitored by the controller
to assess vehicle speed, enabling real-time adjustment of motor revolutions per
minute. A GPS module was incorporated to provide continuous location tracking,
enhancing safety and security (Fig. 1).
Construction
methodology of the extended electric bike
The
fabrication methodology of EEB is presented in Fig. 1.
The dual-drive bicycle is powered by a 48V, 20Ah battery assembled from eight
series-connected 12V cells. Charging can be achieved through plug-in connection,
requiring 4–5 hours, or via the alternator powered by the vehicle’s engine. The
alternator provides direct energy to the motor while recharging the battery. A
boost converter enhances efficiency by regulating voltage and eliminating
harmonics. Once the battery attains full charge, the system automatically
transitions to battery-only operation. The controller regulates motor speed
according to variations in voltage and current, while the GPS module provides
continuous location tracking for improved safety.
Component
analysis
During
construction, an integrated electrical framework was established to facilitate the
reliable performance of the EEB. When the system is
activated, the electric mode becomes operational. The electrical configuration
comprises several core components:
BLDC
hub motor:
A 1000W, 48V hub motor was employed. Hub motors have become increasingly
popular for lightweight electric vehicles, including e-bikes and scooters, due
to their efficiency and compact design (Siddique et al. 2020).
Load-bearing capacity and resistance forces were considered during motor
selection.
Controller
for BLDC hub motor: A
1000W, 48V speed controller was utilized to regulate the hub motor. Brushless
DC motors offer advantages over brushed motors due to electronic commutation,
which allows efficient current switching. The controller enables starting,
stopping, reversing, and precise regulation of torque and speed. Specifications
of the controller are provided in Table 1–2.
Dry
battery: A
12V, 9Ah sealed dry battery with high energy density and leak-proof design was
adopted. Such batteries are widely used in UPS, CCTV, and fire monitoring
systems. In EEB, a combination of these
units was arranged to provide 48V/20Ah, with a discharge capacity of 20A per
hour. The batteries were positioned beneath the seat to conserve space and
maintain balance, thereby supporting eco-friendly operation.
Charger
(AC to DC): The
charger employs a front-end AC-DC converter, allowing connection to a residential
AC supply (Hazarathaiah et al. 2019). This ensures accessibility for
routine charging. Specifications are shown in Table 3.
Fig. 1: Methodology of the system Table 1: Specifications of BLDC Hub motor Specifications Ratings Power 1000 W Torque 18 Nm Peak torque 83 Nm Voltage Operation 48 V Current 23 A Limiting current 38 A RPM 510 Table 2: Specifications of Controller Specifications Rating Voltage 48 V Power 1000 W Phase Angle 120/60o Limiting current 38 A Table 1 Specifications
of a dry battery Rating Voltage 48 V Maximum current 20 A Charging time 3 h Weight 17.6 kg Dimension 5.95×2.56×3.7 inches
Boost
converter: The
boost converter stabilizes voltage, filters harmonics, and improves energy
transfer efficiency, ensuring continuous battery charging during engine
operation.
Self-start
motor: A
self-starting mechanism was implemented to enable ignition without external
assistance. Once combustion is initiated, inertia sustains engine cycles
without requiring repeated starter use.
GPS
module: The
GPS module, integrated as part of the IoT-based security system, provides
anti-theft protection, remote locking, and real-time location monitoring. The
module disables the motor within 10 sec if unauthorized movement occurs.
Additional features include monitoring of charging status and battery
condition.
Bike
frame: The
Honda Pridor was selected as the structural base. This motorcycle is equipped
with an overhead cam four-stroke engine, refined suspension, improved
aerodynamics, and a durable frame. Its robust design made it suitable for
integration with the extended electric system.
Mechanical
design and modeling
Positioning
of electrical and mechanical components presented a key challenge, as
integration was required without compromising aesthetic appearance. Careful
design and adjustments were implemented to arrange components in a manner that
maintained both structural appeal and functional efficiency.
Speed parameters controller
Nominal power=35 kg
Nominal voltages=48 V
Nominal current=30 A
Efficiency = 90%
Protection voltage=60 V
Torque
calculations
Weight of the bike=80 kg
One person's average weight=70 kg
Batteries weight=20 kg
Alternator weight=5 kg
Total weight=m×g……………………….…(1)
Total weight=175×9.81
Total weight=1715 Newtons
Force
required to displace the body
Rolling friction between rubber and coal tar=0.05
F=µ×Total weight acting downward………(2)
F=0.05×1715
F=85.75
Wheel diameter=45.75 cm
Wheel radius=22.875 cm
Torque=r×F……………………………… (3)
Torque=0.227×85.75 cm
Torque=19.4 Nm
On one wheel, it will be=9.73 Nm
Wind load
estimation
The maximum velocity of the design
V (max) = 70 km/h
V (max) = 19.66 m/s
Wind pressure = constant × wind density × V(max)^2……………………………….…
(4)
Wind Pressure = 0.5×1.2×361
Wind Pressure = 216.6N/m^2
Total drag force
Total Drag Force acting on the structure = 19.79 N
Torque load to resist the wind load = 225 × 19.79/4
Torque load to resist the wind load = 1113.18 N-mm
Considering the Frictional load and Inertial load 10%
each
Total torque = derive torque + wind load torque +
frictional torque + inertial torque … … … … (5)
M (t) = 19.4 + 1.1 + (0.1×19.74) + (0.1×19.74)
M (t) = 24.38 Nm
Total tractive effort method for calculating torque
Gross vehicle weight = m×g………………… (6)
Gross vehicle weight = 105×9.81
Gross vehicle weight = 1030N
The weight on each vehicle is derived
W=
1030/2
W = 515 N
Radius of wheel = 22.83 cm
Desired top speed = 20 km/h
Desired to speed=5.5 ms^(-1)
Desired acceleration time = 40 sec
Working surface = Coal tar
Acceleration
force
Acceleration Force
(FA) is the force necessary to accelerate from a stop to maximum speed in the
desired time. The vehicle will perform as designed regarding tractive effort
and acceleration; it must calculate the required wheel torque (TW) based on the
tractive effort.
FA = (Gross weight vehicle × Vmax)/(g
× Time required) …………………………..……… (7)
FA = ((1715 × 5.5))/((9.81 ×
40))
FA = 24.06 W
Wheel motor torque
TW = Resistive torque + Accelerating torque + wind
torque……………………………….……… (8)
TW = 20 + 15.3 + 12.8 = 48.19 Nm
Motor
calculations
Power of motor = torque × speed… (9)
P= 48.19 × 16.6
P= 800 W
Motor selected = 1000 W
Factor of safety = 0.25
Battery calculations
Battery = 48 V
Battery ampere per hour = 20 Ah
Total power = 1000 W
Battery back-up
Battery time = (V × I)/1000……..……(10)
Battery time = (48 × 20)/1000
Battery time = 1 hour (at full speed at full load)
Charging calculations
Power of adopter = V ×I………….…(11)
Power of adopter = 48 × 7
Power of adopter = 336 W
Time to charge = 1000/336
Time to charge = 3 h
Charging at
the alternator
Power for charging = P × I…………(12)
Power for charging = 48 × 1.1
Power = 528 W
Time =
1000/528
Time = 1.8 hour
Efficiency = 800/1000 = 80%
Alternator calculation
Total power = 1000 W + 528 W
Total power = 1528 W
Alternator voltage = 24 V
Alternator ampere = 90 at full speed
At optimum speed = 65 A
Bike mileage
Mileage at petrol = 45 km (in 1 L of petrol and 20%
charge of batteries)
In that 20%, the bike can run 18 km
Total gross mileage at petrol and battery charge = 60 km
(battery) and 63 km (petrol)
Total mileage = 60 + 63 = 123 km
Security
through IoT-based GPS tracking
GPS tracking devices are employed to monitor and record the location of
an object, most commonly when installed in automobiles as part of vehicle
tracking systems. Although it shares certain similarities with car navigation
systems, the two technologies serve distinct purposes. Navigation systems
primarily display the driver’s current location on a digital Table 2: Specification
of AC to DC charger Specifications Rating AC voltage 220 volts DC voltages 55 volts Maximum
current 20 Amperes Table 3: Specification
of the alternator Specifications Rating Voltage 24 V Current 90 A Table 4: Specification
of the boost converter Specifications Rating Power 1000 W Torque 18 Nm Peak Torque 83 Nm Voltage 48 V Current 23 A Limiting current 38 A Table 5: Self-start motor specification Specifications Rating Voltage 12 V Current 5 A Table
6: Specification of the GPS module Specification Rating Operating
voltage 12 V Current 1 mA GPS
positioning precision 10 m Temperature -20oC
to 70oC RH 20–80% Dimensions 6.7
cm*3.88cm*1.15cm Weight 0.125 kg Table 9: Overall comparison of three bikes Design
parameters Extended
electric bike Electric bike IC engine bike Maximum speed 60 km/h 60-65 km/h 100 km/h Lifetime of
battery 5-7 years 5-7 years N/A Physical
weight 105 kg 72 kg 96 kg Energy used Electrical energy or
chemical energy of petrol to convert into mechanical energy Electrical energy The chemical energy of
petrol + chemical gasoline energy to converted into mechanical energy Manufacturing cost Rs. 70,000 Rs. 95,000 Rs. 130,000 Time of charging 2.5 h 2.5 h N/A per km cost Rs. 1.4 Rs. 0.5 Rs. 2.38 Noise during driving 60-100 dB 60-80 dB 80-100 dB Maintenance cost Slightly less Low Slightly high Braking power Good Good HIGH Fuel required YES NO YES Efficiency Best Good Best Effects on environment Slight No Yes Emission of gases Slight No Yes The capacity to carry the
load High Slightly high Very High
SIMULATION AND RESULTS
A voltmeter was used to measure values
in a hardware simulator, which was then simulated using MATLAB R2021b and the
TRINAMIC trainer. A boost converter and a BLDC hub motor were both tested in
this setup. The input and output voltages of the boost converter were measured
with a voltmeter in order to test its operation and to
measure voltage regulation. Some of the operational parameters of the BLDC hub
motor were measured during simulation, such as speed, current, input power,
torque, output power, and efficiency. These were measured with the help of the
voltmeter, TRINAMIC trainer, and other necessary equipment. The general aim of
the simulation was to examine the dynamic operation of the BLDC hub motor,
focusing on speed variation, directional control, current variation over time,
and the maximum achievable speed under load (Table 4–9).
BLDC Hub Motor Simulation
The BLDC hub motor was simulated
in various stages. The speed torque relationship, as shown in Fig. 2–6, was
examined in the first stage. The second stage included applying changing torque
values to the motor and measuring the obtained speeds. The information gathered
was utilized in determining the relationship between motor speed and torque
output, as seen in Fig. 7. The simulation was able to replicate varying
operating conditions by altering torque values in various ranges.
The third phase examined the
interaction between torque and current consumption. Varying torque loads were
imposed upon the motor, and current was measured. The linear correlation
between current and torque, as shown in Fig. 8, sheds light on motor efficiency
and control methods. A fourth test was then performed with the TRINAMIC trainer
to test motor performance at full load. This trainer allowed precise
measurement, in-depth simulations, and real-time feedback. Advanced control
algorithms, accurate data measurement, and light-to-heavy loading flexibility
enabled the system to produce realistic performance for motors. The
velocity–load characteristic is presented in Fig. Fig. 6: Output vs torque Fig. 1: Speed vs. torque Fig.
8:
Speed vs. current Fig. 2: Boost converter Fig. 2: Fabricated Extended Electric Bike Figure 3: Placement of part Fig. 4: GPS-based IoT module
Boost Converter Simulation
Sufficient supply for the BLDC
hub motor and battery charging requirements. In the simulation, a graph was obtained showing output
current and voltage versus input
The primary role of the boost converter in this system
was to elevate the voltage from 24 V to 55 V, ensuring a voltage that
demonstrated the converter’s efficiency across varying conditions. The
converter exhibited stable performance when maintaining an output voltage of 48
V, a current
Practical Results of IoT-Integrated GPS Module
Simulation results also highlighted the integration of
the Burj Track application with the Internet of Things (IoT) and GPS systems.
The module provided real-time monitoring of the vehicle’s location and
performance. Features included mileage tracking, ride playback, and live
updates on parameters such as fuel consumption, engine ON/OFF times, and total
distance traveled. When connected to a mobile device, the system displayed
comprehensive information regarding the vehicle’s operation. Fig. 12 and 13
illustrate simulation results of the Burj Track application under IoT control, demonstrating
its potential to enhance both monitoring and security of the EEB system.
CONCLUSION
In an increasingly resource-constrained and polluted
environment, technologies that optimize motor performance while reducing
operational cost and environmental burden are needed for sustainable, low-cost,
and pollution-free mobility. The integration of alternator-assisted battery
charging and IoT-enabled GPS monitoring significantly improves the overall
utility of the system. The primary objective of this work was to maximize
efficiency at minimal cost, while the secondary objective was to alleviate
environmental strain. Battery units, designed for ease of replacement, ensure
continuous energy availability, and gasoline provides a supplementary source of
power when necessary. Furthermore, the IoT-enabled GPS enhances vehicle
security and provides essential data for system
ACKNOWLEDGMENT
We thank the Department of
Mechatronics and Control Engineering faculty and staff at UET Faisalabad Campus
for providing the necessary guidance and lab facilities.
AUTHOR CONTRIBUTIONS
MS contributed
to conceptualization, methodology design, data curation, and drafting of the
manuscript. MAH performed the experimental setup, conducted performance
analysis, and validated the results. MUK provided critical review, and
technical guidance. MA, MA and ZA carried out
simulations, data interpretation, and figure preparation.
CONFLICTS OF
INTEREST
No conflict of interest among the authors to declare
DATA AVAILABILITY
Data will be made available on a fair request to the
corresponding author
ETHICS APPROVAL
Not applicable to this paper.
FUNDING SOURCE
Self-funded.
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