Electrode Coating Prediction Control for Uniform Slurry Loading
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Solution Overview
Problem
The challenge in the electrode coating process of lithium ion batteries is to achieve uniform slurry loading regardless of the operator's skill level, and to automate the control of slurry temperature to ensure high-quality, high-efficiency products.
Innovation Solution
A prediction control device that includes a data acquisition unit to gather data on the base material and a processor to analyze slurry loading characteristics. The processor derives candidate control values, including slurry temperature, and uses a prediction model to determine the optimal control value based on the quality of the candidate values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual correction work is performed in electrode coating process, then operator skill level affects coating uniformity, but automation requires complex control systems
Solution Approach 1:
The system implements automated feedback control by measuring actual coating thickness and slurry temperature, then adjusting slurry temperature control based on these measurements to maintain uniform coating without requiring complex manual intervention
Solution Approach 2:
The coating system performs self-correction by automatically adjusting slurry temperature based on real-time measurements of coating thickness and temperature, eliminating the need for operator skill-dependent manual correction
2Manufacturing precision
If slurry temperature control is automated, then coating uniformity is improved, but multiple quality elements must be considered together
Solution Approach 1:
The system focuses on controlling slurry temperature as a key parameter that directly affects coating uniformity, while using prediction models to account for the interdependence with other quality elements like coating width and mismatch
Solution Approach 2:
A prediction model acts as an intermediary that processes measurements of coating thickness and temperature to determine appropriate slurry temperature adjustments, managing the complexity of multiple interdependent quality parameters
3Manufacturing precision
If real-time correction is implemented, then coating quality is improved, but measurement and detection complexity increases
Solution Approach 1:
The system replaces complex manual measurement and correction processes with automated sensors that measure coating thickness and slurry temperature, using prediction models to translate these measurements into control actions
Data Source
AI summary
A prediction control device according to an embodiment disclosed herein may include a data acquisition unit acquiring data related to a base material onto which slurry is loaded by using a coating die; and a processor analyzing slurry loading characteristics based on the data, deriving a candidate control value including slurry temperature on the basis of the slurry loading characteristics, predicting a quality of the candidate control value by using a prediction model, and deriving an optimal control value based on the quality.