Electric Motor State Estimation Using Vehicle and Machine Models
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Solution Overview
Problem
Existing methods for determining the rotor angle of electric motors in motor vehicles lack accuracy and reliability, particularly in sensorless systems, which can lead to inefficiencies in torque control and increased costs due to the use of expensive pattern converters.
Innovation Solution
A method and system that utilize vehicle sensors and a machine model of the electric motor to measure and convert data, combining sensorless methods with weighted averaging to determine state variables like rotor angle and rotational speed, thereby improving accuracy and reducing reliance on expensive sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If sensorless methods are used to determine rotor angle, then cost is reduced by avoiding expensive pattern converters, but measurement precision and reliability deteriorate
Solution Approach 1:
The patent combines multiple data sources including vehicle sensors (acceleration sensors, wheel speed sensors), vehicle models, and machine models to determine state variables. This merging of multiple indirect measurement approaches compensates for the lack of direct rotor angle sensors while maintaining acceptable accuracy for control purposes.
Solution Approach 2:
The patent introduces intermediate calculations using vehicle models and machine models that translate readily available sensor data (wheel speed, acceleration) into estimated motor state variables. These models act as intermediaries that bridge the gap between simple sensor measurements and the required rotor angle information.
2Measurement precision
If vehicle sensors and models are used to determine state variables, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent makes existing vehicle sensors (acceleration sensors, wheel speed sensors) serve multiple functions - their primary function for vehicle dynamics control is maintained, and additionally they provide data for electric motor state variable determination. This multi-functionality improves measurement precision without adding dedicated sensors.
Solution Approach 2:
The system uses the vehicle's existing sensor infrastructure and computational resources to serve the additional function of motor control state estimation. The vehicle model and machine model computations leverage available processing power and existing data streams, avoiding the need for separate dedicated systems.
Data Source
AI summary
A method for determining state variables of an electric motor for driving a motor vehicle, comprising the procedural steps: measuring (102, 104) data (103, 105) which comprise information about a current state of vehicle components (10, 12, 30, 40); converting (110) the measured data (103, 105) into data (111) related to the electric motor (10) using a vehicle model of the motor vehicle (1); evaluating (120) the data (111) related to the electric motor (10) using a machine model of the electric motor (10) for determining at least one first state variable (121) of the electric motor (10); determining (130) at least one second state variable (131) of the electric motor (10) using a sensorless method; comparing and assessing for plausibility (140) the at least one first and the at least one second state variable (121, 131).