EV Charging Profile Identification for OEM Adaptation
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Solution Overview
Problem
Current technologies, such as OCPP and IEC 61851-23, do not effectively allow for the identification of a vehicle type during charging, leading to variations in charging behavior and requirements across different OEMs, making reliable charging operations challenging.
Innovation Solution
A method and system that capture and analyze the charging behavior of electric vehicles to create a current charging profile, compare it with stored profiles, and adapt the charging operation based on the identified vehicle type, using sensors, a computer unit, and an optimization unit to ensure OEM-specific implementations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If standardized communication protocols (OCPP, IEC 61851-23) are used for charging, then manufacturer-independent communication is enabled, but vehicle type identification becomes impossible
Solution Approach 1:
The system performs preliminary actions by capturing charging behavior data during the charging operation and creating a charging profile before vehicle type identification is required. This preliminary profiling enables subsequent comparison with stored profiles to identify the vehicle type, thus resolving the contradiction between using standardized protocols and achieving vehicle type identification.
Solution Approach 2:
The system implements feedback by continuously monitoring charging behavior parameters (current, voltage, timing sequences) during the charging operation and using this feedback to create and compare charging profiles. This feedback mechanism enables the system to identify vehicle type even when using standardized communication protocols, as the physical charging behavior provides distinguishing characteristics.
2Reliability
If manufacturer-specific implementations are used to ensure reliable charging, then charging reliability improves, but system complexity increases
Solution Approach 1:
The system changes parameters by adapting charging operation parameters (current limits, voltage levels, timing sequences) based on the identified vehicle type. Instead of implementing multiple manufacturer-specific charging systems, the system uses a single standardized interface that dynamically adjusts charging parameters according to the detected vehicle type, thus improving reliability without increasing system complexity.
Solution Approach 2:
The system applies dynamics by making the charging operation adaptive and dynamic rather than static. The charging profile is created in real-time based on captured behavior, compared with stored profiles, and the charging parameters are dynamically adjusted according to the identified vehicle type. This dynamic approach enables reliable manufacturer-specific charging through a universal standardized interface.
3Measurement precision
If charging behavior is captured and analyzed to create charging profiles, then vehicle type identification accuracy improves, but data processing requirements increase
Solution Approach 1:
The system extracts only the essential charging behavior parameters needed for vehicle type identification, such as current values, voltage values, and timing sequences of connection setup and signal emission. By extracting only these relevant parameters rather than processing all possible charging data, the system achieves accurate vehicle type identification while minimizing data processing requirements.
Data Source
AI summary
A method and system for identifying a vehicle type of a vehicle having an electric drive and a traction battery, in which a charging behavior of the vehicle that occurs during a current operation of charging the traction battery at a charging column is captured. A current charging profile is created for the current charging operation on the basis of the captured charging behavior. The current charging profile is compared with respective charging profiles which are retrievably stored in a storage unit and are each specific to a respective particular vehicle type. A probability of a presence of a particular vehicle type from the plurality of vehicle types is determined on the basis of the comparison. The vehicle type most likely to be present is identified as the vehicle type and the current charging operation is adapted to the vehicle type which is most likely to be present.