DESC:FIELD OF INVENTION
The present invention relates to a super capacitor aided smart charging system for Pedelec type bicycles more particularly the system uses a super capacitor as a primary charging unit and battery as a secondary charging to extend the total battery life, increase the range of battery assist, reduce the size/weight of the battery and partially reduce the final disposal of battery.

BACKGROUND OF INVENTION AND PRIOR ART
There’s already a large body of work on the health benefits of cycling. Studies on what electric bikes can do for our collective and individual health are starting to hit their advance.

The most significant factor is that e-bikes lower the difficulty barrier for people to engage in meaningful, regular exercise. Cresting hills on a bicycle can be daunting even for the very fit, but the power assist from an e-bike ameliorates the challenge. The authors of a study published in the European Journal of Applied Physiology reported that their subjects felt riding electric bicycles was surprisingly fun. Pleasurable activity can translate into positive changes to habits, which could lead to better health outcomes for people who ride e-bikes.

Electric bicycles also provide seniors another option to extend their period of independence. Not only could e-bikes make running their errands possible without relying on an automobile, it also keeps them physically active. Some surprising outcomes regarding the use of e-bikes to alleviate the severity of conditions such as Alzheimer’s and Parkinson’s are coming to light. The model of a power-assisted pedal bike might very well be the ultimate answer for re-engaging large bands of the population with daily physical activity.

From the above observation, the regular riders are using the e-bike as an assisting system.

While electric bicycles may be gaining in popularity, many aspects of electric bicycles technology still may carry drawbacks capable of improvement specifically in the battery technology.

“The proposed invention relates to a Pedelec type bicycle and optimization of battery usage”.

Disadvantages of batteries:
• The biggest disadvantage is that they can only be used for a limited time. Even rechargeable batteries eventually die.
• On the downside, some batteries require maintenance and need to be checked periodically.
• Batteries lead to chemical pollution.
• Rechargeable batteries take time to recharge, and this can be a big hindrance in case of an emergency and
• The batteries can increase the weight of the bicycle.
• In adverse cases, the battery might undergo thermal runaway.

Generally, the Pedelec type bicycle supports the rider via electric power when the rider is fatigued or demanding aid/relief. Naturally, the Pedelec type bicycle does not completely rely on the battery. The proposed patent of introducing the super capacitor further reduces the dependency on the battery.

The prior art US8818601B1 discloses an Extended-range electric vehicle with a supercapacitor as the range extender. This is used for hybrid 4-wheelers. The super capacitors are used as stand-by energy modules rather than to directly power the motors.

OBJECT OF THE INVENTION

An object of the invention is to provide a super capacitor aided smart charging system for Pedelec type bicycles.

Another object of the invention is to use super capacitor as a primary charging unit and battery as a secondary charging unit.

Yet another object of the invention is to extend the total battery life by reducing the total number of charging cycles.

Yet another object of the invention is to increase the range of battery assist while riding the bicycle.

Yet another object of the invention is to reduce the size and weight of the battery by means of super capacitor and smart control system.

Further object of the invention is to indirectly reduce the final disposal requirement rate of the battery.

SUMMARY OF THE INVENTION
Generally, the inventive technology relates to a super capacitor aided smart riding system for Pedelec type bicycles. More particularly, the inventive technology involves novel methods and systems for optimizing battery usage. The inventive technology may be particularly suited to providing supplemental electrical power to the Pedelec type bicycle by providing the super capacitor as a primary charging unit and battery as a secondary charging to extend the total battery life, increase the range of battery assist, reduce the size/weight of the battery and partially reduce the final disposal of the battery.

The super capacitor is used in this embodiment to provide power for the motor. The capacitor can be charged and discharged quickly to provide the required power for the motor. The battery and the capacitor will work in tandem. The decision of which power source takes precedence to supply the motor with power will be controlled by a smart switching circuit.

BRIEF DESCRIPTION OF THE DRAWINGS
S.NO PART NAME PART NO
1. Super capacitor 1
2. Battery 2
3. Motor 3
4. Motor Drive system 4
5. Control system 5
6. Sensors 6
7. Computing device/Mobile device 7
8. Physiological device/Smart watch 8
9. Remote server 9
10. Switching unit 10

Figure 1 illustrates embodiment of the invention which shows the system configuration.
Figure 2 illustrates the embodiment of the invention which shows the basic flow chart of the invention.

The above figures and related written description are not intended to limit the scope of the inventive concepts in any manner. Rather, the figures and written description are provided to illustrate the inventive concepts to a person skilled in the art by reference to particular embodiments.

DETAILED DESCRIPTION OF THE INVENTION
One of the preferred embodiment of the invention discloses about a method being performed in a super capacitor and battery powered pedelec type bicycle having a super capacitor (1), battery (2), motor (3), motor drive system (4), control system (5), plurality of sensors (6), a computing device (7) having a physiological device (8), a remote server (9) and switching unit (10), the method comprises the steps of pairing the control system (5), sensors (6), computing device (7), remote server (9) and physiological device (8) . Allowing the rider by the control system (5) to feed the weight, height, age and health data through the computing device (7). Acquiring the body temperature and heart rate data in real time by means of a physiological device (8). Then acquiring GPS, terrain, gyro, weather and wind velocity data by means of a computing device (7) and the speed, battery percentage, voltage and current data by means of plurality of sensors (6) and also deriving the health statistics data with respect to real time acquired physiological data and manually entered rider data.
The present method mainly characterized for acquiring the riding data and biological data of the rider and mapping the same with charge requirement rate, and each riding cycle being tracked and stored in the remote server (9) along with acquired inputs by the control system (5) to derive machine learning and AI based power source switching pattern to perform the pedal assist through the stored energy of the super capacitor (1) and charge the capacitor (1) while pedaling thereby using the super capacitor (1) as a primary power source and battery (2) as a secondary or backup power source to increase the pedal assist duration, battery life and reduce the battery weight and size. Further the method capable to automatically assisting the pedelec type bicycle according to learned and real time data upon sensing a smart mode.

Another embodiment of the invention discloses about a super capacitor aided smart charging system for pedelec type bicycles consisting of a super capacitor (1), battery (2), motor (3), motor drive system (4), control system (5), plurality of sensors (6), a computing device (7) having a physiological device (8), a remote server (9) and switching unit (10). Wherein the control system (5), sensors (6), computing device (7), remote server (9) and physiological device (8) being paired to acquire
• weight, height, age and health data through the computing device (7),
• acquire a body temperature and heart rate data in real time by means of a physiological device (8),
• acquire GPS, terrain, gyro, weather and wind velocity data by means of a computing device (7),
• acquire the speed, battery percentage, voltage and current data by means of plurality of sensors (6),
• wherein the system derive the health statistics data with respect to real time acquired physiological data and manually entered rider data.
The system mainly characterized to map the real time data, daily riding pattern, calculated and derived data of the rider with charge requirement rate. Wherein each riding cycle being tracked and stored in the remote server (9) along with acquired inputs by the control system (5) to derive machine learning and AI based power source switching pattern to perform the pedal assist through the stored energy of the super capacitor (1) and charge the capacitor (1) while pedaling thereby using the super capacitor (1) as a primary power source and battery (2) as a secondary or backup power source thereby increasing the pedal assist duration, battery life and reduce the battery weight and size and automatically assisting the pedelec type bicycle according to learned and real time data upon sensing a smart mode.

Another preferred embodiment of the invention discloses about a method being performed in a super capacitor and battery powered bicycle having a super capacitor (1), battery (2), motor (3), motor drive system (4), control system (5), plurality of sensors (6), a computing device (7) having a Gyro sensor, GPS and GSM, and a physiological device (8), a remote server (9) and switching unit (10).
The method comprises the steps of;

Step 1: pairing the control system (5), sensors (6), computing device (7), remote server (9) and physiological device (8),

Step 2: allowing the rider by the control system to feed the user data through the computing device,
Step 3: acquiring the real time GPS, terrain, environmental and user data through the plurality of sensors (6) or computing device (7) or physiological device (8) or combination thereof.

Step 4: acquiring the riding data and biological data of the rider and mapping the same with charge requirement rate, and each riding cycle being tracked and stored in the remote server along with acquired inputs by the control system to derive machine learning and AI based power source switching pattern to perform the pedal assist through the stored energy of the super capacitor and charge the capacitor while pedaling thereby using the super capacitor as a primary power source and battery as a secondary or backup power source to increase the pedal assist duration, battery life and reduce the battery weight and size.

Another embodiment of the invention discloses about the biological data capable of being a heart rate or BMI/weight data or concluded rider capability or aerobic and anaerobic respiratory range or combination thereof.

Yet another embodiment of the invention discloses about the physiological device is a smart watch/device which acquires the heartbeat, body temperature, ambient temperature and health statistics.

Yet another embodiment of the invention discloses about the environmental data of the system. The wind velocity is one of the environmental factor which helps to calculate the impacts of drag force while riding.

Yet another embodiment of the invention discloses about the super capacitor aided smart charging system for Pedelec type bicycles consisting of a super capacitor (1), battery (2), motor (3), motor drive system (4), control system (5), plurality of sensors (6), a computing device (7) having a Gyro sensor, GPS and GSM, and a physiological device (8), a remote server (9) and switching unit (10). The said system configured to acquire the real time GPS, terrain, environmental and user data through the plurality of sensors (6) or computing device (7) or physiological device (8) or combination thereof. The system configured to acquire the riding data and biological data of the rider and mapping the same with charge requirement rate, and each riding cycle being tracked and stored in the remote server along with acquired inputs by the control system to derive machine learning and AI based power source switching pattern to perform the pedal assist through the stored energy of the super capacitor and charge the capacitor while pedaling thereby using the super capacitor as a primary power source and battery as a secondary or backup power source to increase the pedal assist duration, battery life and reduce the battery weight and size.

Yet another embodiment of the invention discloses about the pedal assist operation, the capacitor and the battery will work in tandem. With the capacitor being the primary power source.

Yet another embodiment of the invention discloses about various powering action using capacitor, battery and smart control system.
In one aspect, the capacitor will be used to power a Pedelec in tandem with the battery or independently.

Another aspect, the capacitor will be used to power the motor directly.
Yet another aspect, the capacitor will be used to power the motor in tandem with the battery

Further aspect of the system, the capacitor will be used to charge the battery as well as power the motor.

Yet another embodiment of the invention discloses about the switching unit (10) can be controlled in two ways. The first method is by the main control unit/system (5), which will be based on predefined parameters. The second method is through the smart platform which will control for optimum functionality.

Yet another embodiment of the invention discloses about the battery (2) will provide additional power when there is a lack of energy within the capacitor (1) to provide for the hub motor (3). When the cut off speed is reached or when there is no need for the assist, the capacitor (1) will be charged by the hub motor (3).

Yet another embodiment of the invention discloses about the smart learning platform will understand rider tendencies to know preemptively plan the trip along with the power requirement during the trip.

Yet another embodiment of the invention discloses about the smart platform will also work to efficiently switch between regenerative mode to assist mode for the hub motor.

Yet another embodiment of the invention discloses about the capacitor (1) leakage or overcharging, Due to leakage of power from the capacitor (1) and overcharging, the excess energy will be cycled into charging the battery (2) if not required to powering the motor (3).

Yet another embodiment of the invention discloses about the the switching pattern being changed through a relay unit.

Yet another embodiment of the invention discloses about the physiological device (8) is a smart watch or wearable device. The rider data capable of being a weight and height data. In aspect the control system (5) capable of being a micro controller.

In another embodiment of the invention, the environmental data capable of being a wind velocity to calculate the impacts of drag force while riding.

Yet another embodiment of the invention the system prevents unnecessary charging cycle of the battery (2) by means of the super capacitor (1).

Further embodiment of the invention discloses about the battery (2) would provide the additional power in the event the capacitor (1) is unable to provide the total power required to cover the deficiency. The smart platform will also account for the life of the battery to optimally charge the battery to prevent loss of life due to unnecessary charge cycling. This will be in conjunction with the battery management system.

ADVANTAGES
1. The proposed system will increase the total range of power assist during the riding.
2. Total battery life will be extended due to reduced charging cycles.
3. Will be able to use lighter and smaller batteries to meet the same pedal assist range.

So that the manner in which the features, advantages and objects of the invention, as well as others which will become apparent, may be understood in more detail, more particular description of the invention briefly summarized above may be had by reference to the embodiment thereof which is illustrated in the appended drawings, which form a part of this specification. It is to be noted, however, that the
drawings illustrate only a preferred embodiment of the invention and are therefore not to be considered limiting of the invention’s scope as it may admit to other equally effective embodiments.
,CLAIMS:WE CLAIM
1. A method being performed in a super capacitor and battery powered pedelec type bicycle having a super capacitor (1), battery (2), motor (3), motor drive system (4), control system (5), plurality of sensors (6), a computing device (7) having a physiological device (8), a remote server (9) and switching unit (10), the method comprises the steps of ;
a. pairing the control system (5), sensors (6), computing device (7), remote server (9) and physiological device (8) ,
b. allowing the rider by the control system (5) to feed the weight, height, age and health data through the computing device (7),
c. acquiring the body temperature and heart rate data in real time by means of a physiological device (8),
d. acquiring GPS, terrain, gyro, weather and wind velocity data by means of a computing device (7),
e. acquiring the speed, battery percentage, voltage and current data by means of plurality of sensors (6),
f. deriving the health statistics data with respect to real time acquired physiological data and manually entered rider data,
characterized in that
g. acquiring the riding data and biological data of the rider and mapping the same with charge requirement rate, and each riding cycle being tracked and stored in the remote server (9) along with acquired inputs by the control system (5) to derive machine learning and AI based power source switching pattern to perform the pedal assist through the stored energy of the super capacitor (1) and charge the capacitor (1) while pedaling thereby using the super capacitor (1) as a primary power source and battery (2) as a secondary or backup power source to increase the pedal assist duration, battery life and reduce the battery weight and size.
h. automatically assisting the pedelec type bicycle according to learned and real time data upon sensing a smart mode.

2. A super capacitor aided smart charging system for pedelec type bicycles consisting of a super capacitor (1), battery (2), motor (3), motor drive system (4), control system (5), plurality of sensors (6), a computing device (7) having a physiological device (8), a remote server (9) and switching unit (10),
• wherein the control system (5), sensors (6), computing device (7), remote server (9) and physiological device (8) being paired to acquire
o weight, height, age and health data through the computing device (7),
o acquire a body temperature and heart rate data in real time by means of a physiological device (8),
o acquire GPS, terrain, gyro, weather and wind velocity data by means of a computing device (7),
o acquire the speed, battery percentage, voltage and current data by means of plurality of sensors (6),
o wherein the system derive the health statistics data with respect to real time acquired physiological data and manually entered rider data,
characterized in that
• wherein the system maps the real time data, daily riding pattern, calculated and derived data of the rider with charge requirement rate,
• wherein each riding cycle being tracked and stored in the remote server (9) along with acquired inputs by the control system (5) to derive machine learning and AI based power source switching pattern to perform the pedal assist through the stored energy of the super capacitor (1) and charge the capacitor (1) while pedaling thereby using the super capacitor (1) as a primary power source and battery (2) as a secondary or backup power source thereby increasing the pedal assist duration, battery life and reduce the battery weight and size and automatically assisting the pedelec type bicycle according to learned and real time data upon sensing a smart mode.

2. The system as claimed in claim 2, wherein the switching pattern being changed through a relay unit.

3. The system as claimed in claim 2, wherein the physiological device (8) is a smart watch or wearable device.

4. The system as claimed in claim 2, wherein the rider data capable of being a weight and height data.

5. The system as claimed in claim 2, wherein the control system (5) capable of being a micro controller.

6. The system as claimed in claim 2, wherein the environmental data capable of being a wind velocity to calculate the impacts of drag force while riding.

7. The system as claimed in claim 2, wherein the super capacitor configured to power the drive unit or battery or combination thereof.

8. The system as claimed in claim 2, wherein the smart mode capable to enable regenerative mode for generating power.

9. The system as claimed in claim 2, wherein the capacitor’s (1) the excess energy being used for charging the battery (2) if not required to powering the motor (3).

10. The system as claimed in claim 2, wherein the system prevents unnecessary charging cycle of the battery (2) by means of the super capacitor (1).