Electric Drive Train Torque Control for Gear Noise Aging
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Solution Overview
Problem
The challenge of addressing noise development due to aging or wear in electric motor drive trains, particularly in electric vehicles, where changes in tooth stiffness over time are not initially reflected in torque control, leading to noticeable noise that existing methods fail to adequately dampen.
Innovation Solution
A method for operating an electric motor drive train that detects changes in tooth stiffness through operating state signals, using a classification algorithm to adapt torque control by superimposing a periodic torque change signal in phase with tooth stiffness changes, adjusting the control signal to counteract noise development.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If a periodic torque change signal is superimposed on the control signal to dampen gear noise, then noise at tooth meshing frequencies is reduced, but the effectiveness of noise damping deteriorates over time due to wear and aging changes in tooth stiffness
Solution Approach 1:
The patent implements dynamic adaptation of the torque change signal parameters based on detected tooth stiffness. The control system continuously monitors tooth stiffness through vibration analysis and adjusts the torque signal characteristics accordingly, transforming a static control approach into a dynamic one that evolves with the drivetrain's condition
Solution Approach 2:
The patent establishes a feedback loop where vibration sensors detect tooth stiffness changes, the control unit processes this information, and adjusts the torque change signal parameters in response. This closed-loop system ensures the noise damping remains effective despite wear and aging by continuously adapting to actual tooth stiffness conditions
2Object-affected harmful factors
If the amplitude of the periodic torque change signal is increased to improve noise damping, then gear noise is reduced, but tonal noise from variable tooth stiffness increases with transmitted torque
Solution Approach 1:
The patent dynamically adjusts parameters of the torque change signal including amplitude, frequency, and phase based on detected tooth stiffness. By optimizing these parameters rather than using fixed values, the system achieves effective noise damping while minimizing the generation of tonal noise that would result from excessive or mismatched torque variations
3Device complexity
If no additional sensors are used and existing signals are relied upon for torque estimation, then device complexity is reduced, but measurement precision of tooth stiffness changes deteriorates over time due to wear
Solution Approach 1:
The patent replaces direct mechanical measurement of tooth stiffness with an indirect measurement approach using electrical signals. By analyzing existing motor current, voltage, and position signals through sophisticated algorithms, the system detects tooth stiffness changes without adding mechanical sensors to the drivetrain
Solution Approach 2:
The control unit acts as an intermediary that processes existing electrical signals to extract tooth stiffness information. Rather than directly measuring mechanical properties, the system uses electrical signal analysis as an intermediate step to infer mechanical condition, avoiding the need for additional mechanical sensing equipment
Data Source
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AI summary
The invention relates to a method for operating a drive train (2) having an electromotive drive (4), wherein a speed and a drive torque of the electromotive drive (4) can be converted via a toothed transmission stage (12) for an output (19), and the electromotive drive (4) is controlled with a control signal (40), wherein a periodic torque change signal (5) which alternately reduces and amplifies the drive torque is superimposed on the control signal (40) in order to damp transmission noises, wherein the periodic torque change signal (5) is in phase with a periodic change in the tooth stiffness of the toothed transmission stage (12). The method according to the invention proposes, on the basis of a software architecture extended by machine-learning knowledge, detecting a change in state of the drive train over the service life that can be attributed to a long-term change in the tooth stiffnesses of the transmission stage, and based on these changes, to adjust a torque control in such a way that progressive noise effects caused by ageing or wear can be better damped.