Vehicle Air Conditioning Control Device Predicting Passenger Load
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Solution Overview
Problem
Existing vehicle air conditioning control devices either compromise on energy saving and power saving or vehicle interior comfort, failing to provide comprehensive control that balances all three aspects effectively.
Innovation Solution
A vehicle air conditioning control device that includes a target environment setter, environment detectors, condition predictors, thermal load calculators, and power predictors to calculate and adjust air conditioning output commands based on vehicle interior and exterior conditions, passenger load, and power usage, ensuring optimal comfort while minimizing energy and power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If feedback control is performed to enhance air conditioning capacity after detecting temperature increase, then vehicle interior comfort is improved, but time lag occurs between detection and effective air conditioning
Solution Approach 1:
The control device predicts the passenger load factor at the next station in advance and pre-activates the air conditioning compressor before the vehicle arrives at the next station. This preliminary action ensures that air conditioning is already effective when passengers board, eliminating the time lag between temperature detection and cooling activation.
2Reliability
If air conditioning compressor is started in advance based on predicted passenger load factor, then vehicle interior comfort is maintained, but energy consumption increases
Solution Approach 1:
The control device dynamically adjusts the air conditioning output command value based on real-time power consumption data and predicted future power consumption. The system activates or adjusts air conditioning only when predicted power consumption indicates available surplus power, making the energy usage flexible and adaptive rather than fixed or continuous.
Solution Approach 2:
The control device continuously monitors actual power consumption and feeds this information back to adjust the air conditioning output command value. This feedback mechanism ensures that air conditioning operation is continuously optimized based on real power availability, preventing unnecessary energy consumption while maintaining comfort when power is available.
3Use of energy by moving object
If air conditioning control prioritizes energy saving and power saving, then energy consumption is reduced, but vehicle interior comfort is compromised
Solution Approach 1:
The system predicts power consumption in advance and pre-activates air conditioning during periods when surplus power is expected to be available. This ensures that comfort is maintained during low-power-consumption periods without compromising energy savings during high-demand periods.
Solution Approach 2:
The control device changes the air conditioning output parameter dynamically based on the balance between predicted power consumption and comfort requirements. When predicted power consumption shows surplus capacity, the system increases cooling output to maintain comfort; when power consumption is high, it reduces output to save energy.
Data Source
AI summary
A vehicle air conditioning control device calculates, through a thermal load calculating unit, a vehicle interior thermal load Q on the basis of, for example, a vehicle interior temperature Tin, a vehicle interior humidity Hin, a vehicle exterior temperature Tout, a passenger load factor θ, and a vehicle-interior-temperature set value Tset. Through an air conditioning output calculating unit, the vehicle air conditioning control device calculates an output command value for an air conditioner on the basis of a vehicle-interior-temperature upper-limit value Tmax, a vehicle-interior-temperature lower-limit value Tmin, the thermal load Q, power-running/regenerative electric power P, and then, corrects the calculated output command value for the air conditioner on the basis of power-running/regenerative electric power Pf at or after a prediction time point and of a passenger load factor θf at or after the prediction time point.