Micro-Mobility Power Control for Adaptive Source Switching
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Solution Overview
Problem
Micro-mobility vehicles lack a system for automating the activation of electrical and human power sources based on user-defined objectives, leading to inefficient and jarring user experiences.
Innovation Solution
A power optimization system that utilizes a processor to receive user objectives, recognize input device data, determine optimal characteristics, and apply them to optimize power parameters, including feedback to the user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If the user manually controls the electrical power source activation based on personal preference, then the system simplicity is maintained, but the power utilization efficiency deteriorates
Solution Approach 1:
The system automatically determines and switches between electrical and human power sources based on real-time input device data and user objectives, eliminating the need for manual user control decisions. The processor autonomously optimizes power source selection by analyzing cadence, power, speed, and battery charge data against stored objective parameters, thereby improving power utilization efficiency without requiring complex manual intervention systems
Solution Approach 2:
The system continuously monitors input device data points from sensors and feedback devices, comparing real-time performance against stored objective parameters to dynamically adjust power source activation. This closed-loop feedback mechanism enables automatic optimization of power utilization while maintaining manageable system complexity through algorithmic control rather than mechanical complexity
2Loss of energy
If the electrical power source is turned off to conserve battery, then the energy consumption is reduced, but the user experience deteriorates due to reliance on human power
Solution Approach 1:
The system dynamically adjusts electrical power source activation based on real-time conditions and user objectives stored in the system. Rather than static on/off control, the processor continuously evaluates input device data (cadence, power, speed, battery charge) against objective parameters to determine optimal power source engagement, enabling adaptive battery consumption management that maintains smooth transitions and pleasant user experience across varying ride conditions
Solution Approach 2:
The system changes operational parameters by switching between different power source configurations based on real-time data and stored objectives. The processor modifies power delivery parameters, cadence thresholds, and activation criteria dynamically, allowing the system to optimize battery consumption while maintaining user experience through parameter adjustment rather than abrupt power source changes
3Productivity
If the system automates power source activation based on user objectives, then the power optimization is improved, but the device complexity increases
Solution Approach 1:
The system stores multiple objective parameters in advance (e.g., maximum battery charge, maximum cadence, maximum power, maximum speed, minimum journey time) before the ride begins. The processor selects and applies the appropriate pre-stored objective based on user preference, eliminating the need for complex real-time objective formulation algorithms while achieving effective power optimization through pre-configured performance targets
Solution Approach 2:
The system uses a single processor to perform multiple functions: collecting input device data, storing objective parameters, determining optimal characteristics, controlling power source activation, and providing feedback. This multi-functional approach consolidates what could be separate complex subsystems into one integrated unit, improving power optimization while managing overall system complexity through functional integration
4Loss of information
If the system provides real-time feedback to the user, then the user awareness of optimal performance is improved, but the information processing requirements increase
Solution Approach 1:
The system extracts and displays only the most relevant optimal characteristic information to the user through feedback devices, rather than presenting all raw data and computational results. The processor identifies key performance indicators and actionable insights from the optimization process, presenting simplified feedback that informs users about optimal performance without requiring them to process complex computational data
Data Source
AI summary
A micro-mobility vehicle power optimization system generating and applying a set of optimal characteristics. The system comprises a processor. The processor is operable to carry out the steps of: receiving, from an input from a user of the micro-mobility vehicle, an objective parameter; recognising, from the micro-mobility vehicle, a set of input devices; determining, from the set of input devices, a set of input device data points; storing, on a datastore, the set of input device data points; determining the set of optimal characteristics; applying, to the set of input devices, the optimal characteristics, thereby optimizing the power parameters of the set of input devices of the micro-mobility vehicle. The optimal characteristics are determined based on: the objective parameter; and the set of input device data points.