Onboard Digital Twin Control for Real-Time Vehicle Component Simulation
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Solution Overview
Problem
Conventional vehicle component management systems rely on preexisting datasets derived from predefined test conditions, which fail to emulate real-world scenarios, leading to overdesigned components and conservative control strategies, resulting in inefficient resource utilization.
Innovation Solution
A digital twin system onboard a vehicle that includes a processor circuit and memory, executing physics-based simulations of vehicle components to dynamically modify control strategies based on real-time data and simulations, optimizing component operations and energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If preexisting datasets from predefined test conditions are used for component management, then component design safety is improved, but resource utilization efficiency deteriorates
Solution Approach 1:
The patent creates a digital twin (a virtual copy) of the physical vehicle system that replicates its behavior and characteristics. This digital replica allows for virtual testing and simulation without affecting the actual vehicle, enabling more efficient component design and testing while maintaining safety through realistic scenario emulation.
Solution Approach 2:
The system performs preliminary virtual testing and validation through physics-based simulations in the digital twin environment before implementing changes in the actual vehicle. This allows component designs and control strategies to be optimized in advance, reducing the need for extensive physical testing and improving resource utilization.
2Stability of the object's composition
If preexisting datasets from predefined test conditions are used for control strategies, then system stability is improved, but operational efficiency deteriorates
Solution Approach 1:
The control strategy transitions from static preexisting datasets to dynamic real-time simulations. The digital twin continuously simulates vehicle behavior under current operating conditions, allowing the control strategy to adapt dynamically while maintaining stability through physics-based models that accurately represent system behavior.
Solution Approach 2:
The system implements closed-loop feedback by continuously comparing actual vehicle performance with simulated behavior in the digital twin. This feedback mechanism allows for real-time optimization of control strategies while maintaining system stability through validated physics-based models that predict system response to control changes.
3Productivity
If physics-based simulations are executed in real-time onboard, then operational efficiency is improved, but computational resource requirements increase
Solution Approach 1:
The digital twin system segments the vehicle into discrete simulated components (powertrain, thermal systems, battery, etc.) that can be simulated independently and in parallel. This modular approach reduces computational complexity while maintaining overall system accuracy, enabling real-time simulation onboard the vehicle.
Solution Approach 2:
The system adjusts simulation parameters and model fidelity based on operational context and available computational resources. During normal operation, simplified models are used for real-time control, while more detailed simulations can be performed when computational resources are available or for offline analysis, optimizing the balance between accuracy and computational demand.
Data Source
AI summary
A method includes executing, by an Electronic Control Unit (ECU) of a vehicle, a physics-based simulation of a first simulated component of a plurality of simulated components of a digital twin including a plurality of corresponding simulated components, the first simulated component corresponding to a first physical component of a plurality of physical components of the vehicle. The method further includes modifying, by the ECU, a control strategy for operation of the vehicle to modify an operation of the vehicle based on the simulation of the first simulated component. The method further includes executing, by the ECU, the modified control strategy to control the first physical component.