Thermodynamic Block Models for Scalable BMS Commissioning
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Solution Overview
Problem
Conventional building management systems (BMS) rely on point-based models that require extensive commissioning, lack scalability, and have high capital costs, providing minimal extractable information for advanced control strategies.
Innovation Solution
A BMS utilizing thermodynamic models, where each device stores a thermodynamic block with connections and stats, allowing for calculations and simulations to manage building performance, and a controller sums outputs from atomic blocks to model subsystem performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If point-based models are used to represent building data, then data can be captured and stored, but considerable commissioning time is required to define and configure each point
Solution Approach 1:
The patent uses look-up tables to store pre-defined point definitions and relationships, allowing the system to copy and reuse standardized data structures rather than manually configuring each point. This dramatically reduces commissioning time while maintaining data representation capability.
Solution Approach 2:
The system transitions from manual point-by-point configuration to automated parameter-based modeling using thermodynamic equations. By changing the fundamental approach from discrete point configuration to continuous parameter modeling, the system eliminates extensive commissioning requirements.
2Ease of manufacture
If point-based models with look-up tables are used, then data storage is simplified, but sufficient definition is lacking to provide meaning to data points
Solution Approach 1:
The patent combines multiple data elements into composite thermodynamic models that include equipment specifications, operational parameters, and performance relationships. This composite approach provides comprehensive data meaning while maintaining structured storage efficiency.
Solution Approach 2:
The thermodynamic models serve multiple functions simultaneously: they store data, define relationships, enable calculations, and provide performance predictions. This multi-functionality eliminates the need for separate look-up tables while providing rich data meaning.
3Loss of information
If conventional point-based model architecture is used, then minimal extractable information is provided, but advanced control strategies cannot be effectively implemented
Solution Approach 1:
The patent implements dynamic thermodynamic models that continuously calculate equipment performance based on real-time operating conditions. These dynamic models provide extractable information for control strategies by modeling equipment behavior across varying conditions rather than static point values.
Solution Approach 2:
The thermodynamic models enable feedback-based control by calculating predicted equipment performance and comparing it with actual measurements. This feedback mechanism provides the extractable information needed for advanced control strategies to optimize building system performance.
4Reliability
If point-based models require closed control loops to function properly, then control accuracy is maintained, but capital cost increases and scalability is reduced
Solution Approach 1:
The thermodynamic models perform self-calibration and self-validation by comparing calculated performance with actual sensor data. This self-service capability maintains control reliability without requiring complex closed-loop architectures, reducing system complexity and improving scalability.
Solution Approach 2:
The system performs preliminary calculations using thermodynamic models to predict equipment performance before actual operation. This preliminary action provides control guidance that maintains reliability while reducing the complexity of real-time closed-loop control requirements.
Data Source
AI summary
A building management system (BMS) includes one or more sensors that measure a variable state or condition in the BMS and a plurality of BMS devices that operate to affect the variable state or condition measured by the one or more sensors. Each of the BMS devices stores a thermodynamic block that models the BMS device. Each of the thermodynamic blocks includes a list of connections and a list of stats. The connections define one or more inputs to the thermodynamic block and one or more outputs from the thermodynamic block. The stats define one or more relationships between the inputs and the outputs. Each of the BMS devices includes a solver configured to perform calculations using the stats and connections defined by the thermodynamic block stored within the BMS device.