Transport Climate Control Energy Prediction for Route Sufficiency
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Solution Overview
Problem
Users of transport climate control systems face uncertainty regarding the sufficiency of energy to maintain desired climate conditions during a route, leading to potential energy depletion and load loss, especially when the energy storage source is not fully charged.
Innovation Solution
A method and system that provide predictive energy consumption feedback by obtaining route parameters, determining expected energy consumption, and comparing it to the available energy level, with alerts and notifications displayed via a human-machine interface to inform users about energy sufficiency or depletion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the energy storage source is not fully charged before departure, then vehicle availability increases, but the risk of energy depletion and load loss during transit increases
Solution Approach 1:
The system performs preliminary energy consumption calculations before departure by obtaining route parameters (duration, door openings, ambient temperature, set point) and comparing expected consumption against available energy. This advance assessment allows vehicles to be dispatched with partially charged batteries when sufficient energy is predicted, increasing availability while maintaining reliability through informed decision-making.
Solution Approach 2:
The system provides continuous feedback to users through a human-machine interface, displaying alerts when expected energy consumption exceeds available energy, and showing current energy levels throughout the route. This feedback loop enables operators to make informed decisions about route selection and timing, preventing energy depletion while maximizing vehicle utilization.
2Adaptability or versatility
If the transport climate control system operates with limited energy, then operational flexibility increases, but the likelihood of climate control failure increases
Solution Approach 1:
Before each route, the system calculates expected energy consumption based on route-specific parameters including duration, number of door openings, ambient temperature, and set point conditions. This preliminary assessment allows the system to determine whether the energy storage source is sufficient for the intended operation, enabling flexible routing decisions while ensuring climate control reliability by avoiding routes that would deplete energy.
Solution Approach 2:
The system continuously monitors and displays current energy levels throughout the route via the human-machine interface, providing real-time feedback on energy sufficiency. This enables operators to adjust operations dynamically and take preventive action before energy depletion occurs, maintaining climate control reliability while preserving operational flexibility.
3Reliability
If real-time energy monitoring and predictive feedback are implemented, then energy management reliability improves, but system complexity increases
Solution Approach 1:
The controller performs multiple functions using existing system components: it obtains route parameters from the human-machine interface, calculates energy consumption based on standard operational parameters, monitors energy levels from the energy storage source, and provides feedback through the existing display interface. This multi-functional approach improves energy management reliability without requiring separate dedicated systems for each function.
Solution Approach 2:
The system uses its own existing infrastructure (controller, human-machine interface, energy storage management) to perform energy assessment and monitoring functions. Rather than requiring external complex systems, the climate control system itself generates the predictive feedback, thereby improving reliability while minimizing additional complexity.
Data Source
AI summary
Systems and methods are provided for providing predictive energy consumption feedback for powering a transport climate control system. 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. The route parameters may be obtained via a human-machine interface. When the energy storage source is less than the expected energy consumption, a user is alerted. The systems and methods may further compare the energy level to an expected energy level during transit to determine if the energy level is greater or less than expected and alert the user when the energy level is less than expected.