Lithium-Ion Battery Pack Charging Current Optimization for Fast Safe Charging
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Solution Overview
Problem
Conventional lithium battery charging methods are inefficient, prone to overcurrent charging, and fail to minimize battery damage due to fixed parameters and lack of consideration for the battery's actual state, leading to slow charging speeds and low efficiency.
Innovation Solution
A multi-target simultaneous charging method for lithium battery packs that uses a charging weight coefficient to convert energy loss and current into a quadratic programming problem, solved using an interior point method and adaptive momentum gradient descent algorithm to optimize the charging current sequence, ensuring the shortest convergence and charging times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If constant current charging is used, then charging speed is improved, but battery damage increases due to overcurrent charging
Solution Approach 1:
The patent implements dynamic charging current adjustment by dividing charging into multiple stages with different current levels. The charging current is dynamically changed based on charging progress and battery state, transitioning from high current in early stages to lower current in later stages, thereby maintaining fast charging speed while preventing battery damage from excessive current
Solution Approach 2:
The patent changes charging parameters (current magnitude and duration) across different charging stages. By adjusting current parameters dynamically - using higher current initially and reducing current as charging progresses - the system optimizes both charging speed and battery safety, resolving the contradiction between fast charging and battery protection
2Reliability
If constant voltage charging is used, then battery safety is improved, but charging speed decreases
Solution Approach 1:
The patent employs dynamic voltage adjustment across charging stages rather than maintaining constant voltage throughout. In early charging stages, higher voltage is applied to achieve faster charging, while voltage is reduced in later stages to ensure battery safety, thus dynamically balancing speed and reliability
Solution Approach 2:
The charging process is divided into periodic stages with different voltage and current characteristics. Each stage has specific parameter ranges that are periodically applied, allowing the system to achieve fast charging during safe periods while ensuring battery protection during critical periods
3Reliability
If multi-stage charging is used, then battery safety is improved, but charging time increases
Solution Approach 1:
The patent optimizes the duration and parameter transitions of each charging stage dynamically. By carefully controlling the time spent in each stage and smoothly transitioning between stages, the system achieves comprehensive battery protection while minimizing total charging time, preventing excessive prolongation despite multiple stages
4Productivity
If charging current is increased, then charging efficiency is improved, but polarization phenomenon worsens
Solution Approach 1:
The patent implements dynamic current adjustment that adapts to battery state changes. By increasing current when the battery can accept it (reducing polarization impact) and adjusting current based on real-time feedback, the system maximizes charging efficiency while managing polarization effects through dynamic control rather than fixed current
Data Source
AI summary
Disclosed in the present invention is a multi-target simultaneous charging method for a lithium battery pack: converting energy loss and charging current into a lithium battery pack charging cost model with a charging weight coefficient, and using an interior point method for solving and processing to acquire a preset charging current sequence; on the basis of the preset charging current sequence, calculating the charging time required when charging the lithium battery pack, and adjusting the charging weight coefficient in the lithium battery pack charging cost model by means of an adaptive momentum gradient descent algorithm to obtain the charging weight coefficient with the shortest charging time; using the charging weight coefficient to optimize the lithium battery pack charging cost model to acquire a new preset charging current sequence; and using the new preset charging current sequence to implement charging, thereby implementing optimized multi-target simultaneous charging of the lithium battery pack.