Determining battery or solar panel capacity for an electric refrigeration unit
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Solution Overview
Problem
Determining the optimal battery and solar panel capacity for electric refrigeration units is challenging due to variable weather conditions, thermal dynamics, and delivery cycle parameters, leading to inefficiencies and high costs in existing hybrid systems.
Innovation Solution
A computerized method simulates thermal performance and energy requirements over historical weather data to determine the required battery and solar panel capacity, optimizing their combination to meet energy demands while minimizing costs and resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If large capacity batteries are installed to provide capacity for long journeys, then the energy supply reliability is improved, but the device complexity and cost increase
Solution Approach 1:
The battery system is divided into multiple modular battery packs that can be individually managed and combined. Each battery pack operates as an independent unit with its own management system, allowing the overall system to scale flexibly based on journey requirements without requiring a single large complex battery system.
Solution Approach 2:
The battery configuration is made dynamic through the ability to add or remove battery packs based on the specific journey requirements. The system can adapt its capacity from small configurations for short trips to larger configurations for long journeys, optimizing both reliability and complexity for each operational scenario.
2Productivity
If fast chargers are installed to minimize downtime between journeys, then the productivity is improved, but the device complexity and cost increase
Solution Approach 1:
The charging system is segmented into multiple independent charging ports and channels, allowing multiple battery packs to be charged simultaneously through different pathways. This modular charging architecture increases productivity without requiring a single complex fast charging system.
Solution Approach 2:
The battery management system automatically manages charging operations, prioritizing and scheduling charging tasks without manual intervention. The system can autonomously determine which battery packs need charging and route them to appropriate charging resources, reducing the complexity of charging management while maintaining high productivity.
3Reliability
If very large batteries and solar panels are installed to cater for all eventualities, then the energy supply reliability is improved, but the manufacturing cost and resource use increase
Solution Approach 1:
The system uses dynamic configuration where the number and capacity of battery packs and solar panels are adjusted based on the specific journey requirements and environmental conditions. Rather than installing fixed oversized components, the system scales its energy infrastructure to match actual needs, reducing manufacturing costs while maintaining reliability through on-demand capacity adjustment.
Solution Approach 2:
The system changes operational parameters such as battery capacity configuration and solar panel deployment based on predicted weather conditions, journey duration, and energy consumption patterns. This allows the system to optimize between reliability and manufacturing cost by adapting its configuration rather than relying on fixed oversized components.
4Use of energy by moving object
If the number and size of batteries and solar panels are increased to maximize efficient use of solar energy, then the use of energy is improved, but the device complexity and cost increase
Solution Approach 1:
The energy management system incorporates continuous feedback loops that monitor solar energy generation, battery charge levels, and energy consumption patterns. This feedback enables the system to dynamically adjust the configuration and operation of batteries and solar panels to maximize solar energy utilization while maintaining manageable complexity through automated control algorithms.
Solution Approach 2:
The system dynamically adjusts the operational parameters of batteries and solar panels based on real-time conditions, such as optimizing charge/discharge cycles and solar panel orientation or activation. This dynamic approach maximizes solar energy use without requiring permanently oversized or overly complex fixed configurations.
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
This approach ensures efficient use of solar power, reduces redundant capacity, and lowers total cost of ownership by providing a high degree of statistical confidence in meeting energy requirements, thus enabling a shift away from diesel-powered refrigeration units.
Implementation Method 1
determining solar panel capacity for an electric refrigeration unit... the electrical refrigeration unit drawing power from the solar panels and from rechargeable batteries
Implementation Method 2
battery capacity of one or more rechargeable batteries for an electric refrigeration unit... the electrical refrigeration unit being of a type configured to draw power from the rechargeable batteries
Implementation Method 3
the TRU typically consists of four primary components for the refrigeration cycle: evaporator, compressor, condenser, and expansion valve. When the compressor is driven, these combine to chill air in one or more compartments in the interior of the trailer
Data Source
AI summary
A computerized method for determining battery and/or solar panel capacity for configuring an electric refrigeration unit. The electrical refrigeration unit is configured to draw power from rechargeable batteries and solar panels in cooling a mobile enclosure interior. Input data is received relating to the location in which the refrigeration unit is to be deployed, historical weather data for the location, and a desired delivery cycle for the refrigeration unit. Thermal performance of the enclosure is simulated based on its thermal properties to output energy requirements for cooling the enclosure to the set point temperature of the delivery cycle for a particular historical day. Energy requirements for delivery cycles are iteratively simulated on plural historical days and energy to be supplied by batteries to meet the energy requirements is determined. Battery and/or solar panel capacity for storing sufficient energy to meet energy requirements for each delivery cycles is calculated.