Vehicle Digital Twin Interface Personalization for Drive Train Control
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Solution Overview
Problem
Existing digital twin systems for passenger vehicles are limited in their ability to enhance customer experience and offer primitive interfaces that do not allow for user-specific configuration.
Innovation Solution
A system that includes a digital twin interface capable of representing various operating states of a vehicle to the user, utilizing a digital twin system that receives vehicle parameter data to determine these states, and an identity management system to customize the interface based on the user's profile.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a digital twin system is implemented to represent vehicle operating states, then the ability to simulate and analyze vehicle operation is improved, but the interface remains primitive and does not allow for user-specific configuration
Solution Approach 1:
The digital twin interface is made dynamic and adaptable by introducing an identity management system that automatically configures the interface based on user profiles. The system transitions from a static, one-size-fits-all interface to a dynamic, user-specific interface that adjusts its presentation and functionality according to the authenticated user's preferences and role, thereby resolving the contradiction between maintaining simulation accuracy and enabling interface configurability.
Solution Approach 2:
The interface parameters are changed from fixed to variable based on user identity. The identity management system modifies interface parameters such as displayed information, interaction modes, and configuration options according to the authenticated user's profile, allowing the same digital twin system to provide personalized experiences while maintaining its core simulation capabilities.
2Ease of operation
If a configurable digital twin interface is implemented to allow user-specific customization, then user satisfaction is improved, but the system complexity increases
Solution Approach 1:
The identity management system operates autonomously to configure the digital twin interface based on user profiles without requiring manual setup or complex user interventions. The system automatically authenticates users, retrieves their preferences, and customizes the interface accordingly, thereby improving ease of operation while minimizing the complexity burden on users.
Solution Approach 2:
The identity management system acts as an intermediary layer between the user and the digital twin interface. This intermediary handles the complexity of user authentication, profile management, and interface configuration automatically, shielding users from system complexity while enabling personalized experiences.
3Adaptability or versatility
If multiple user profiles are supported with customized interfaces, then adaptability to different users is improved, but the time required for interface configuration increases
Solution Approach 1:
User profiles and interface preferences are pre-configured during the user setup phase. When users authenticate, the system retrieves their pre-saved preferences and immediately applies them to customize the digital twin interface, eliminating the need for time-consuming configuration during each session and enabling rapid adaptation to different users.
Solution Approach 2:
The system implements feedback mechanisms where user interactions and preferences are continuously learned and stored in their profiles. This feedback loop allows the system to automatically refine and personalize the interface based on past behavior, reducing the time required for configuration in subsequent sessions while maintaining high adaptability.
Data Source
AI summary
A system may include sensors, provided on a vehicle, to sense one or more operational states of the vehicle and output the sensed operational states. A system may include a cloud computing platform to receive the sensed operational states, a modeling application, provided at the cloud computing platform, having a processor to execute software to generate and operate a digital twin of the vehicle, the digital twin encompassing twin subsystems of the vehicle and simulating operations thereof; and an artificial intelligence system, associated with the cloud computing platform, to receive and process the sensed operational states and updates an operational parameter of the drive train of the vehicle based on the modeling application.