“实验-仿真-算法”三元融合下的绿色能源领域拔尖创新研究生培养模式探索与实践

康振烨; 毛思含; 刘云; 王旻; 石文娟; 王天娇; 袁禹亮; 李静; 饶鹏; 史晓东; 田新龙

doi:10.19799/j.cnki.2095-4239.2025.1146

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“实验-仿真-算法”三元融合下的绿色能源领域拔尖创新研究生培养模式探索与实践

储能学科建设 | 更新时间：2026-07-13

- “实验-仿真-算法”三元融合下的绿色能源领域拔尖创新研究生培养模式探索与实践
- Exploration and practice of an elite innovative graduate training model in the field of green energy based on the triadic integration of ‘Experimentation-Simulation-Algorithms’
- 储能科学与技术 2026年15卷第6期页码：2421-2429
- 作者机构：
  
  1.海南大学海洋技术与装备学院
  2.海南大学机电工程学院
  3.海南大学化学化工学院，海南海口 570228
  4.中国石油大学，（华东）新能源学院，山东青岛 266580
- 作者简介：
  
  康振烨（1988—），男，博士，教授，研究方向为氢能技术，E-mail：zkang@hainanu.edu.cn；
  王旻，副教授，研究方向为氢能技术与应用，E-mail：minwang@upc.edu.cn
  田新龙，教授，研究方向为海洋清洁能源，E-mail：tianxl@hainanu.edu.cn。
- 基金信息：
  
  海南省高等学校教育教学改革研究资助项目(Hnjg2025ZC-4;Hnjg2025ZD-11);海南大学2025年度学位与研究生教育教学改革研究项目(HDJG-Y202518);中国石油大学（华东）研究生教育教学改革项目(YJG2025008);国家自然科学基金面上项目(22579043)
- DOI：10.19799/j.cnki.2095-4239.2025.1146
  中图分类号： G 420
- 收稿：2025-12-22，
  
  修回：2026-01-18，
  
  纸质出版：2026-06-28
- 稿件说明：
移动端阅览
康振烨, 毛思含, 刘云, 等. "实验-仿真-算法"三元融合下的绿色能源领域拔尖创新研究生培养模式探索与实践[J]. 储能科学与技术, 2026, 15(6): 2421-2429.

KANG Zhenye, MAO Sihan, LIU Yun, et al. Exploration and practice of an elite innovative graduate training model in the field of green energy based on the triadic integration of 'Experimentation-Simulation-Algorithms'[J]. Energy Storage Science and Technology, 2026, 15(6): 2421-2429.
康振烨, 毛思含, 刘云, 等. "实验-仿真-算法"三元融合下的绿色能源领域拔尖创新研究生培养模式探索与实践[J]. 储能科学与技术, 2026, 15(6): 2421-2429. DOI： 10.19799/j.cnki.2095-4239.2025.1146.

KANG Zhenye, MAO Sihan, LIU Yun, et al. Exploration and practice of an elite innovative graduate training model in the field of green energy based on the triadic integration of 'Experimentation-Simulation-Algorithms'[J]. Energy Storage Science and Technology, 2026, 15(6): 2421-2429. DOI： 10.19799/j.cnki.2095-4239.2025.1146.

摘要

为应对“碳达峰碳中和”目标下绿色能源技术快速发展对高层次人才的紧迫需求，解决传统工科研究生培养中存在的学科壁垒森严、理论与实践脱节、创新能力不足等突出问题，本研究以质子交换膜电解水（PEMWE）这一国家战略前沿方向为例，系统构建并实践了一种“实验-仿真-算法”三元融合的研究生培养新模式。该模式以真实复杂的工程问题为牵引，通过“课程体系重构-多导师协同指导-闭环迭代训练-产教融合支撑”四位一体的实施路径，引导学生贯通材料工程、多物理场仿真与智能优化算法三大知识模块，形成“理性设计-精准制备-高效验证”的研究闭环。实践表明，该模式显著激发了学生的内在创新驱动力，培养的研究生不仅取得了多项学术成果，更具备了解决复杂工程科学问题的“融合设计”能力与系统思维。本研究为“新工科”背景下储能、氢能等交叉领域拔尖创新人才培养提供了可复制、可推广的实践范式，特别是为储能科学与工程这类高度复杂系统的研究生培养提供了直接借鉴，对推动工程教育内涵式发展、服务国家重大战略需求具有重要参考价值。

Abstract

This paper aims to address the urgent demand for high-level talents in green energy technologies under the carbon peaking and neutrality goals and address prominent problems in traditional engineering postgraduate education

such as rigid disciplinary barriers

disconnection between theory and practice

and insufficient innovation capability. To this end

it proposes and implements a novel triadic integration training "experimentation–simulation–algorithm" for postgraduate students. Considering proton exchange membrane water electrolysis

a national strategic frontier

as an example

this model is driven by complex real-world engineering challenges. Through a four-in-one implementation path comprising curriculum restructuring

multisupervisor collaborative guidance

closed-loop iterative training

and industry–education integration support

the algorithm guides students toward integrating three core knowledge modules: materials engineering

multi-physics simulation

and intelligent optimization algorithms

thereby forming a closed research loop of "rational design–precision fabrication–efficient verification." An analysis of the model's implementation reveals that it significantly stimulates students' drive for intrinsic innovation. Graduates achieved outstanding academic outcomes and developed "convergent design" capabilities and systems-based thinking to solve complex engineering and scientific problems. This study proposes and tests a replicable and scalable practical paradigm for cultivating high-quality innovative talents in interdisciplinary fields such as energy storage and hydrogen energy in the "Emerging Engineering Education" context

offering an important reference for promoting connotative development of engineering education and therefore serving major national strategic needs.

关键词

Keywords

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