Vehicle Zone Climate Control Using Predicted Occupancy
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Solution Overview
Problem
Climate control systems in autonomous vehicles face challenges in balancing passenger comfort with energy efficiency, particularly in scenarios where occupancy changes frequently, such as in robotic taxis, leading to inefficiencies in energy use and comfort maintenance.
Innovation Solution
A dynamic climate control system that adjusts settings based on predicted occupancy changes, using data such as vehicle booking characteristics, journey types, and ambient conditions to optimize temperature and comfort in occupied and unoccupied vehicle regions, minimizing active regulation while ensuring comfort for future users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the climate control system actively regulates the climate in unoccupied regions to maintain comfort, then passenger comfort is improved, but energy consumption increases
Solution Approach 1:
The system performs preliminary climate regulation in unoccupied regions based on predicted occupancy. Before a passenger enters, the system proactively adjusts the climate settings in their designated region to the preferred temperature, so that when they enter, the comfort condition is already established. This eliminates the need for continuous active regulation and reduces energy consumption while maintaining comfort reliability.
Solution Approach 2:
The climate control system dynamically adjusts its regulation strategy based on real-time occupancy status and predictions. When a region is unoccupied, the system reduces or suspends active climate regulation to save energy. When occupancy is detected or predicted, the system activates climate control in that specific region. This dynamic adaptation resolves the contradiction by making the system efficient during unoccupied periods while ensuring comfort when needed.
2Use of energy by moving object
If the climate control system suspends active regulation in unoccupied regions to conserve energy, then energy efficiency is improved, but comfort readiness deteriorates
Solution Approach 1:
The system uses occupancy prediction data to perform preliminary climate adjustments before passengers enter. By predicting which regions will be occupied and when, the system proactively sets the appropriate climate conditions in advance. This ensures comfort readiness is maintained without requiring continuous active regulation, thus preserving energy efficiency while avoiding comfort delays.
Solution Approach 2:
The system incorporates feedback from occupancy sensors and prediction algorithms to continuously monitor and adjust climate settings. When occupancy is detected or predicted in a previously unoccupied region, the system receives feedback and activates climate control in that region. This feedback mechanism ensures that comfort readiness is maintained without unnecessary energy consumption during truly unoccupied periods.
3Use of energy by moving object
If the climate control system adjusts settings based on predicted occupancy changes, then energy efficiency is improved, but system complexity increases
Solution Approach 1:
The climate control system integrates multiple functions into a unified control architecture. The same control unit that manages climate regulation also processes occupancy sensor data and executes prediction-based decision-making. By making the climate control system multi-functional, the patent avoids adding separate dedicated systems for occupancy detection and prediction, thereby improving energy efficiency without proportionally increasing system complexity.
Solution Approach 2:
The system uses its own existing sensors and processing capabilities to perform occupancy detection and prediction, rather than relying on external complex systems. The climate control unit leverages available vehicle data (sensor readings, journey information) to make predictions and adjust settings autonomously. This self-service approach enables energy-efficient predictive control while minimizing the addition of external complex subsystems.
Data Source
AI summary
There is provided a method comprising: determining an occupancy status of a first region of a vehicle; determining, based at least in part on the occupancy status, a first climate control setting for the first region; controlling a climate control system of the vehicle to adjust a climate of the first region according to the first climate control setting; determining that a second region of the vehicle is unoccupied, wherein the second region is fluidly connected to the first region; determining a second climate control setting, wherein the second climate control setting is based at least in part on the occupancy status of the first region and characteristic data associated with a predicted potential change in occupancy status for the second region; and controlling the climate control system to adjust a climate of the second region according to the second climate control setting.