Transport Climate Control Energy Forecasting for Route Completion
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Solution Overview
Problem
Users of transport climate control systems face uncertainty regarding whether the system has sufficient energy to maintain desired climate conditions during a route without a stop for energy refreshment, leading to risks of load loss when energy runs out in transit.
Innovation Solution
A method and system that provide energy consumption feedback by obtaining route parameters and external data such as weather and traffic conditions, determining expected energy consumption, and comparing it to the stored energy level, displaying messages or suggesting remedial measures like alternate routes or set point adjustments to ensure route completion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of stationary object
If the transport climate control system operates without stopping to refresh energy storage, then the system can maintain continuous climate control during transit, but the risk of energy depletion increases leading to potential load loss
Solution Approach 1:
The system performs preliminary energy consumption calculations before route execution by integrating route parameters (distance, elevation, stops), weather forecasts, and traffic predictions to determine expected energy consumption. This advance assessment allows users to know whether the energy storage source can complete the route without stopping, enabling informed decisions about route acceptance or energy refreshment.
Solution Approach 2:
The system provides feedback by comparing the expected energy consumption against the available energy storage level and communicating this information to the user through a display interface. This feedback mechanism enables users to understand the energy status and make decisions about whether to proceed with the route or take actions to refresh energy storage before departure.
2Measurement precision
If external data such as weather and traffic conditions are integrated into energy consumption calculations, then the precision of energy estimation improves, but the system complexity increases
Solution Approach 1:
The controller serves multiple functions: it obtains route parameters from various sources, integrates external data (weather forecasts, traffic predictions), performs energy consumption calculations, compares results against energy storage levels, and provides user feedback. By consolidating these diverse functions into a single controller, the system achieves high measurement precision without proportionally increasing overall system complexity.
Solution Approach 2:
The system uses an intermediary approach by obtaining external data through communications links to remote servers rather than directly processing raw data streams. This intermediary layer simplifies the complexity by providing processed, relevant information (forecasts and predictions) that can be directly used in energy calculations without requiring complex real-time data processing infrastructure.
3Productivity
If routing software integration is implemented to match transport units with routes based on energy levels, then fleet operational efficiency improves, but the complexity of route management systems increases
Solution Approach 1:
The routing software automatically matches transport units with suitable routes based on their energy storage levels without requiring manual intervention. The system self-evaluates whether available energy is sufficient for proposed routes and makes appropriate matchings, thereby improving fleet operational efficiency while keeping the complexity manageable through automated decision-making algorithms.
Data Source
AI summary
Systems and methods are provided for providing energy consumption feedback for powering a transport climate control system using external data. This can include determining whether an energy level of an energy storage source is greater than an expected energy consumption of a transport climate control system during a route, based on route parameters and route conditions. The route conditions may be obtained from a source such as a remote server, and include data such as weather data, traffic data, or the like. The systems and methods may further compare current energy levels to an updated predictions of energy consumption during transit to determine if the energy level is sufficient to complete the route and alert the user when the energy level is insufficient to complete the route.