Wearable Sensor Control for Electric Ride-On Vehicle
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Solution Overview
Problem
Existing electric foot-deck-based vehicles require manual operation of remote controls, which can be awkward and interfere with the rider's balance, and often rely on pressure sensors that necessitate specific movements, limiting intuitive control and safety features.
Innovation Solution
A powered foot-deck vehicle equipped with a wearable remote sensor unit, such as a smartphone with a gyroscope and accelerometer, that transmits orientation and movement data wirelessly to a motor control unit, allowing intuitive control through natural movements like leaning and providing a safety feature to slow down if the rider moves away from the vehicle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a hand-held remote control is used to control the electric skateboard, then the vehicle can be controlled remotely, but the operation becomes awkward and interferes with the rider's balance
Solution Approach 1:
The patent replaces the mechanical hand-held remote control system with a wearable sensor unit that detects rider movements through accelerometers and gyroscopes. This substitution eliminates the need for manual remote control operations, allowing riders to control the skateboard intuitively through natural body movements while maintaining safety and control.
Solution Approach 2:
The sensor unit worn by the rider automatically detects and transmits movement data to the control system without requiring manual intervention. The system serves itself by automatically interpreting rider movements and translating them into control commands, eliminating the need for separate control operations.
2Ease of operation
If pressure sensors are used to detect rider movement, then the vehicle can respond to rider input, but specific movements are required which limits intuitive control
Solution Approach 1:
The patent replaces pressure sensors with wearable inertial measurement units (IMUs) that use accelerometers and gyroscopes to detect three-dimensional movement. This substitution enables the system to detect a broader range of natural rider movements including leaning, shifting weight, and body orientation changes, providing more intuitive and versatile control without requiring specific foot or body positioning.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables intuitive and safe operation by responding to natural rider movements without the need for pressure sensors or manual control panel operation, enhancing the riding experience and safety by automatically slowing down if the distance between the sensor unit and motor control unit exceeds a predefined limit.
Implementation Method 1
The remote sensor unit can comprise a three-axis gyroscope, and the sensor data can comprise the orientation of the remote sensor unit
Implementation Method 2
The remote sensor unit can comprise a three-axis accelerometer, and the sensor data can comprise the movement of the remote sensor unit
Implementation Method 3
The wireless transmission module can communicate with the motor control unit via the Bluetooth wireless technology standard
Data Source
AI summary
In an aspect, a powered vehicle is provided, and includes a body to support a rider. At least one wheel is rotatably coupled to the body to enable travel of the body over a travel surface. At least one motor is coupled to at least one of the at least one wheel to drive rotation thereof. A power source is coupled to the at least one motor to power the at least one motor. A remote sensor unit is wearable by the rider and configured to detect at least one of an orientation, a position, and movement of the rider and transmit sensor data generated therefrom. A motor control unit is coupled to the at least one motor and is configured to receive the sensor data and control the operation of the at least one motor based at least in part on the sensor data.