AI-BASED WIRELESS CHARGING STATION FOR ELECTRIC VEHICLES

Abstract

ABSTRACT The invention presents an Al-based wireless charging system for electric vehicles, designed to enhance charging efficiency in high-traffic urban environments. The system consists of a wireless power transmitter at the charging station and a wireless power receiver· in the electric vehicle. The AI system dynamically adjusts power delivery based on real-time data from sensors, including battery status, environmental conditions, and vehicle alignment. The system utilizes a wireless sensor network for vehicle detection and queue management, offering a cost-effective, scalable solution for public and private charging locations

Specification

DETAILED DESCRIPTION
Title of the Invention
"AI-Based Wireless Charging Station for Electric Vehicles"
Technical Field
The present invention relates to the field of electric vehicle (EV) charging
technology, specifically wireless power transfer systems. More particularly, the
invention focuses on an artificial intelligence (AI)-driven, wireless charging solution
that optimizes the power transfer process between the charging station and electric
vehicles. The system leverages real-time data, wireless communication, and AI
algorithms,Jo improve the efficiency, safety, and user experience of charging electric
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vehicles ih'lurban environments. This invention is applicable to public and private
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spaces, in?Iuding parking lots, malls, theaters, and residential areas, where
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traditional-wired charging infrastructure may pose challenges.
Field of Invention.
ThSiiinvcntion is positioned within the rapidly growing sector of electric
.· -~ vehicle (~J') infrastructure, which includes wireless power transfer systems aild Atbased
sm~..h, systems for EV charging optimization. More specifically, it addresses
the need "I or wireless charging solutions that adapt to the dynamic conditions of
urban environments and optimize power transfer using intelligent, real-time
decision-making capabilities.
Background of the Invention
As global initiatives to reduce carbon emissions and reliance on fossil fuels
have gained momentum, the adoption of electric vehicles has increased
dramatically. This shift has led to a growing demand for efficient and scalable EV
charging solutions. Traditional wired EV charging systems, although widely
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deployed, present several limitations:
Wired charging stations require substantial infrastructure, including physical
connections and specific layouts, which can be both costly and space-consuming.
This is especially problematic in densely populated urban areas, where space IS
limited, and the installation of physical charging points becomes impractical.
Current wireless charging solutions lack advanced optimization capabilities.
They typically transfer power at fixed rates, without considering real-time factors
such as battery condition, environmental variables, or the presence of multiple
vehicles in the queue.
In existing charging systems, users may experience delays and inefficiencies
due to long queues, inconsistent charging speeds, or incomplete charge notifications,
leading to longer-than-expected wait times.
Given these limitations, there is a pressing need for an intelligent, AI -based wireless
charging solution that not only reduces the physical infrastructure required but also
optimizes the charging process based on real-time data and predictive algorithms.
Summary of the Invention
The invention provides an AI -driven wireless charging station for electric
vehicles, designed to offer a cost-effective, scalable, and highly efficient charging
solution. The system comprises two major components: the transmitter (AI Tx side)
installed at the charging station and the receiver (EV vehicle side) installed within
the electric vehicle. The AI system dynamically adjusts the power transfer process
based on real-time inputs, ensuring optimal charging while minimizing energy
wastage and charging time .
The system uses a Wireless Sensor Network (WSN) for vehicle detection and
status monitoring. The AI algorithm analyzes the data from various sensors,
including voltage, current, and environmental factors, to predict charging times,
manage queues, and adjust power delivery dynamically. This Al-powered charging
station is particularly suitable for high-traffic locations, such as parking lots in
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malls, theaters, and parks, where space and infrastructure limitations often pose
challenges to conventional EV charging solutions.
Block Diagram of AI Tx Side: The AI Tx side illustrates the key components of
the wireless charging station, including the. IR parking sensor, ATMega328
controller, AI -based software analyzer, wireless transceiver, and. wireless power
transmitter (WPT Tx). These components work together to detect vehicle presence,
initiate the charging process, and optimize power transfer
Block Diagram of EV Vehicle Side: The EV vehicle side block diagram represents
the components of the wireless power receiver system installed in the electric
vehicle. It includes the wireless power receiver (WPT Rx), ATMega328 controller, ·
voltage and current sensors, wireless transceiver, and relay driver, which together
control and monitor the power reception process.
Detailed Description of the Invention
System Architecture
The AI -based wireless charging station consists of two primary components:
the Transmitter Side (AI Tx) and the Receiver Side (EV Vehicle). Each of these
components is responsible for facilitating the wireless power transfer process while
ensuring that the entire system operates efficiently and safely under AI supervision. ·
Transmitter Side (AI Tx Side)
The transmitter side, installed at the charging station, comprises several key
components that work together to initiate and control the charging process.
)> The IR sensor detects the presence of a vehicle in the designated parking
space. When a vehicle is detected, the sensor sends a signal to the
ATMega328 controller, which triggers the system to initiate wireless power
transfer.
)> The controller serves as the central processing unit for the transmitter side. It
processes data from the parking sensor and controls the operation of the
wireless power transmission module. Additionally, it communicates with the
AI-based software analyzer to optimize power transfer based on real-time
feedback.
)> This module utilizes machine learning algorithms to analyze real-time data
from the sensors and make adjustments to the power delivery. The AI system
predicts the charging time based on battery levels, vehicle specifications, and
environmental conditions (such as temperature). By adjusting the power
output dynamically, the AI system ensures efficient charging and minimizes
energy waste.
)> The WPT Tx module transmits power wirelessly to the vehicle's rece1ver
(WPT Rx) using inductive coupling technology. The transmitter adjusts its
power output in real-time, as dictated by the AI -based software.
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~ The transceiver enables wireless communication between the charging station
and the vehicle. It transmits data such as battery status, power consumption,
and charge completion notifications.
~ The relay driver controls the safe transfer of power to the vehicle, ensuring
that power is only transmitted when a vehicle is present and properly aligned
for charging. It also disengages the power when charging is complete.
~ The LCD display provides real-time feedback to the user, showing the battery
status, charge completion time, and system alerts. It also displays any errors
or system issues for troubleshooting purposes.
Receiver Side (EV Vehicle Side)
The receiver side is installed within the electric vehicle and works in
conjunction with the transmitter to receive power and communicate charging status.
~ The WPT Rx module receives power wirelessly from the WPT Tx module
and converts it into electrical energy for the vehicle's battery. The receiver
ensures that power is transferred efficiently and safely.
~ The on-board controller monitors the power reception process and
communicates with the AI system at the transmitter side to ensure that power
is transferred at optimal levels. It also processes data from the voltage and
current sensors .
~ These sensors continuously monitor the charging process, ensuring that the
battery is being charged at a safe and consistent rate. They prevent
overcharging and overheating by communicating real-time data to the
A TMega328 controller.
~ The wireless transceiver exchanges data with the charging station, providing
real-time updates on the battery's charging status, temperature, and power
levels. This data is essential for the AI system to make necessary adjustments
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)> Similar to the transmitter side, the relay driver on the receiver side ensures
safe power management, controlling the connection and disconnection of the
wireless power receiver.
)> The LCD display on the vehicle provides the owner with real-time updates,
including the current charge level, estimated time for full charge, and
notifications for when the charge is complete.
AI-Powered Optimization
The core innovation of this system lies in its AI -based software, which
optimizes the charging process. The AI system utilizes historical data and real-time
inputs from the sensors to:
)> The system calculates the approximate time required to fully charge the
vehicle based on battery status, power consumption, and environmental
conditions.
)> By adjusting the power output dynamically, the AI system ensures that energy
is used efficiently, preventing overcharging, power loss, or excessive energy
draw.
)> In high-traffic locations, the AI system manages multiple vehicles by
prioritizing those witil the most depleted batteries or based on user
preferences.
Safety Features
Safety is a critical aspect of the system, with multiple layers of protection.
The AI system monitors real-time data to prevent overcharging and overheating.
The system automatically disengages power transfer if any anomalies are detected,
· such as improper vehicle alignment, unauthorized vehicle access, or electrical
surges.
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CLAIMS
Claim 1: A wireless charging system for electric vehicles, comprising:
~ A wireless power transmission module integrated into the charging station;
~ A wireless power reception module integrated into the electric vehicle;
~ A controller configured to initiate and monitor wireless power transmission;
~ An artificial intelligence system for optimizing charging based on real-time
data;
~ A wireless sensor network for detecting vehicle presence, monitoring
charging status, and adjusting power output.
Claim 2: The system of claim I, wherein the AI system dynamically adjusts power
output based on real-time battery data, environmental conditions, and historical
charging patterns.
Claim 3: The system of claim I, further comprising voltage and current sensors to
monitor charging parameters and ensure efficient and safe power transfer.
Claim 4: The system of claim I, wherein a relay driver controls the initiation and
termination of power transfer to prevent overcharging or power wastage.
Claim 5: The system of claim I, further comprising a user interface, such as an
LCD display or mobile application, to provide real-time· charging data and
notifications to the vehicle owner

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