Predictive Vehicle Preconditioning for Battery and Cabin Comfort
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Solution Overview
Problem
Vehicles often fail to provide optimal comfort upon entry due to varying climates, leading to driver discomfort and potential inefficiencies in battery usage, as they are not pre-conditioned before use.
Innovation Solution
A system that utilizes a processor to analyze schedules and user behavior to predict when a vehicle will be used, allowing for pre-conditioning of the interior temperature and battery, thereby improving comfort and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the vehicle is pre-conditioned before use, then driver comfort is improved, but energy consumption increases
Solution Approach 1:
The system performs preliminary action by pre-conditioning the vehicle interior temperature and battery before the driver enters or uses the vehicle. The processor predicts upcoming key-on events and initiates climate control and battery heating/cooling in advance, so that when the driver enters, the vehicle is already comfortable and the battery is optimally charged, resolving the contradiction between comfort and energy efficiency.
Solution Approach 2:
The system uses feedback by continuously monitoring actual key-on events and comparing them with predicted key-on events. When deviations are detected (actual usage differs from prediction), the system updates its prediction model and adjusts future pre-conditioning decisions, optimizing the balance between comfort provision and energy consumption based on real-world usage patterns.
2Ease of operation
If the vehicle pre-conditions based on predicted usage, then driver comfort is improved, but system complexity increases
Solution Approach 1:
The system performs self-service by automatically predicting driver usage patterns and initiating pre-conditioning without requiring driver input or interaction. The processor autonomously analyzes historical data, predicts key-on events, and controls vehicle systems, eliminating the need for complex user interfaces or manual scheduling while maintaining simplicity for the end user.
Solution Approach 2:
The system replaces mechanical or manual scheduling methods with electronic prediction algorithms. Instead of requiring physical buttons, switches, or manual climate control adjustments, the patent uses software-based prediction and automated electronic control to manage pre-conditioning, reducing mechanical complexity while improving functionality.
3Use of energy by moving object
If the vehicle waits for actual key-on event, then energy efficiency is maintained, but driver comfort deteriorates
Solution Approach 1:
The system performs preliminary action by pre-conditioning the vehicle interior temperature and battery before the driver enters or uses the vehicle. The processor predicts upcoming key-on events and initiates climate control and battery heating/cooling in advance, so that when the driver enters, the vehicle is already comfortable and the battery is optimally charged, resolving the contradiction between comfort and energy efficiency.
Solution Approach 2:
The system applies dynamics by making the pre-conditioning strategy adaptive rather than static. The processor dynamically adjusts pre-conditioning decisions based on predicted probability of key-on events, current vehicle state, and environmental conditions. This dynamic approach allows the system to optimize comfort provision while managing energy consumption flexibly according to real-time and historical data.
Data Source
AI summary
A system includes a processor configured to access a schedule of vehicle start times. The processor is also configured to select a scheduled key-on time, when a current time is within a tunable proximity to the scheduled key-on time. Further, the processor is configured to determine if a present vehicle-related temperature warrants vehicle preconditioning and precondition the vehicle until preset preconditioning settings are established.