基于临界点定量识别的电池组梯次利用最优储能路径规划方法

The identification of critical points and the planning of energy storage paths are the key parts to construct the ecological chain for cascade utilization of battery packs during their life cycles. However, nowadays they are depends strongly on the experience, lacking quantitative evaluation tools and systematic optimization methods. This project is presented from the perspectives of the quantification, modelling and optimization of the life cycle management of battery packs. In this project, the key factors for capacity fading of battery packs and their variation rules are explored, and the quantitative relationship between key factors and capacity fading is established through experimental study and forecasting-regression modelling of the capacity fading of battery packs. Then, the effects of the capacity fading characteristics, the electricity supplies and demands on capacity configuration are illustrated, and a flexible design method for capacity configuration of energy storage system with batches of battery packs is developed via subperiod partitioning and multiperiod synthesis. At last, after studying the influences of capacity fading characteristics and capacity configuration on the economic and environmental benefits of cascade utilization of battery packs, a systematic method of optimal critical point identification and energy storage path planning for cascade utilization of battery packs is proposed by dynamic modelling and optimization. This project will also expected to provide a new thought for the synthesis and optimization problems in energy and chemical industries and its relevant fields.

电池组梯次利用的临界点识别和储能路径优选是构建电池组全生命周期梯次利用生态链的关键环节。但目前仍凭借经验确定，缺乏定量的分析工具和系统的优化方法。本项目拟从电池组全生命周期管理的定量化、模型化和最优化角度出发，通过对电池组容量衰退过程的实验研究和回归-预测模型构建，探究电池组容量衰退的特征影响因素及变化规律，构建电池组容量衰退与其特征影响因素间的定量关联关系；通过对电池组储能系统的操作周期划分和多周期集成模型构建优化，阐明电池组容量衰退特性、系统供电和用电特性对储能容量配置的影响机制，构建多批次电池组储能容量的柔性设计方法；通过对电池组梯次利用过程的动态模型构建与求解，探究电池组容量衰退特性和电池组储能容量配置对电池组梯次利用全生命周期经济和环境效益的影响特性，构建电池组梯次利用最优临界点的定量识别和最优储能路径规划方法。本项目的研究也将为能源化工及相关领域集成和优化问题的求解提供新思路。

本项目从电池组全生命周期管理的定量化、模型化和最优化角度出发，构建了基于电池容量衰退特性的动力电池梯次利用退役点的识别和储能场景优选的系统方法。通过研究锂离子电池的容量衰退机理，建立了基于电化学-热耦合的锂离子电池两阶段容量衰退模型，实现了锂离子电池容量衰退过程非线性转折点的定量估计，明确了电池容量衰退全过程的关键影响因素;通过耦合电池组的容量衰退、系统的供电和用电行为的时均特性和波动特性，提出了多种类电池储能系统容量配置的通用设计和优化方法，阐明了系统的供需特性对多种类电池储能系统设计和操作的影响机制；面向多负载需求的储能场景，提出了多种类退役电池储能系统的拓扑重构设计方法和操作优化方法，明确了退役电池储能系统的拓扑结构与负载需求间的对应匹配规律，以及电池容量衰退特性与系统操作优化间的相互影响关系；针对电池梯次利用全过程，构建了动力电池梯次利用的全生命周期评价模型，提出了动力电池梯次利用退役点定量识别的多目标优化方法，阐明了储能场景和电池使用终点对退役点选择的影响。以上研究成果不仅为电池组的梯次利用提供了定量的分析工具和优化方法，也可为能源、化工等相关领域内系统特征因素的识别、定量关系的构建以及系统的集成和优化提供新的研究思路。