Vehicle Climate Control Using Geolocation and Passenger Load Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current climate control systems in transport vehicles lack autonomous optimization capabilities, failing to efficiently adjust to real-time ambient conditions and passenger/load data, leading to suboptimal environmental control within the vehicle.
Innovation Solution
A method and system that utilize a controller to receive geolocation-specific data, climate control data, and passenger/load data to generate adjustment instructions for the climate control system, determining the optimal operating mode based on projected internal space humidity and ambient temperature, thereby adjusting the system's operation to maintain a comfortable environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If climate control systems operate without autonomous optimization, then system simplicity is maintained, but energy efficiency and adaptability to real-time conditions deteriorate
Solution Approach 1:
The climate control system autonomously monitors ambient conditions, internal space parameters, and passenger load data to automatically adjust its operation without manual intervention or complex external control systems, enabling the system to self-optimize energy efficiency
Solution Approach 2:
The system continuously receives feedback from sensors monitoring ambient temperature, humidity, internal space conditions, and passenger count/duration, using this feedback to dynamically adjust climate control operations for optimal energy efficiency
2Adaptability or versatility
If climate control systems lack real-time data integration, then system complexity is reduced, but adaptability to changing environmental and passenger conditions deteriorates
Solution Approach 1:
The climate control system integrates multiple data sources (ambient conditions, internal sensors, passenger load information) into a single control framework that adapts to various operating scenarios, making the system universally applicable to different environmental and operational conditions
Solution Approach 2:
The system dynamically adjusts climate control parameters based on real-time changes in ambient conditions, internal space environment, and passenger load characteristics, enabling continuous adaptation to varying operational requirements
3Reliability
If climate control systems do not project future humidity levels, then computational requirements are reduced, but passenger comfort optimization deteriorates
Solution Approach 1:
The system performs preliminary calculations to project future internal space humidity levels based on current conditions and expected passenger load, allowing proactive adjustment of climate control parameters before comfort degradation occurs
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
The solution enables autonomous optimization of climate control systems in transport vehicles, improving passenger comfort and energy efficiency by dynamically adjusting to real-time conditions and passenger loads, ensuring optimal environmental conditions within the vehicle.
Implementation Method 1
The refrigeration circuit includes a compressor, an exterior heat exchanger, and an interior heat exchanger
Data Source
Figure 1A
Figure 1B
Figure 2
AI summary
A method for autonomous climate control optimization of a transport vehicle having a climate control system is provided. The method includes a controller receiving geolocation specific data providing location information of the transport vehicle. The method also includes the controller receiving climate control data providing operational status information of the climate control system. The method also includes the controller receiving passenger/load data providing passenger/load information travelling in the transport vehicle. Also, the method includes the controller generating adjustment instructions of the climate control system based on the geolocation specific data, the climate control data, and the passenger/load data. Further, the method includes adjusting operation of the climate control system based on the adjustment instructions.