电池组预测性能源管理博士研究员
Predictive energy management of battery packs
原帖优先：申请材料、截止时间与资格以原帖和学校官方说明为准。
博士招生与资助公告
- 申请年度
- 2027；原帖说明：How to apply Apply now You need to: • choose programme type (Research), 2027/28, Faculty of Engineering and Physical Sciences • select Full time or Part time • search for programme PhD Engineering & the Environment (7175) • add name of the supervisor in section 2 of the application Applications should include: • your CV (resumé) • 2 academic references • degree transcripts and certificates to date • English language qualification (if applicable)
- 最近申请截止
- 2027-04-30
- 全部申请截止
- （Europe/London）
- 资助原文
- Fees and funding We offer a range of funding opportunities for both UK and international students. Horizon Europe fee waivers automatically cover the difference between overseas and UK fees for qualifying students. Competition-based Presidential Bursaries from the University cover the difference between overseas and UK fees for top-ranked applicants. Competition-based studentships offered by our schools typically cover UK-level tuition fees and a stipend for living costs for top-ranked applicants. Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered. For more information, please visit our postgraduate research funding pages.
- 资助条件
- 原帖为竞争性或附条件资助说明，未确认本项目获资助及申请人能获奖；不作为保证全奖。
- 原帖材料说明
- • your CV (resumé)
- • 2 academic references
- • degree transcripts and certificates to date
- • English language qualification (if applicable)
确定性信息来自对应版本的完整原帖。原帖只提供日期，日末和学校当地时区为本站转换假设。筛选使用最后申请截止；资助与录取以学校审核结果为准。
AI 中文速览
- 研究内容
- 本项目开发了一种用于锂离子电池的预测性电池热管理系统，结合了固态珀尔贴元件与混合人工智能控制器。通过预测模型预测热负载，并利用决策算法优化珀尔贴元件的运行以最大限度地减少寄生能量，并通过 MATLAB/Simulink 仿真和实验进行验证，旨在实现更安全、更长寿、更高能效的电能存储。
- 申请条件
- 申请人需持有英国 2:1 荣誉学士学位或其国际同等学历。
- 待遇
- 提供竞争性奖学金资助，通常涵盖英国本土学费以及用于生活成本的津贴；总统奖学金和 Horizon Europe 费用减免可为符合条件的优秀申请者补足海外与英国学费之间的差额。
- 申请方式
- 申请人需通过学校系统在线申请，选择研究型项目、2027/28 学年、工程与物理科学学院，选择全职或兼职，搜索项目 PhD Engineering & the Environment (7175)，并在申请第二部分添加导师姓名。
- 材料清单
- 个人简历 (CV)
- 2封学术推荐信
- 迄今为止的学位成绩单与证书
- 英语语言资格证明（如适用）
由 gemini-2.5-flash-lite 生成，博士岗判定置信度 100%。
岗位信息
- 最终轮次截止
- 2027-04-30
- 学科
- 能源
- 合同类型
- 项目资助
- 本站收录
- 内容更新
- 原帖导师候选（待核验）
- Richard Wills, Iris Nandhakumar
- 来源
- 南安普顿大学博士研究项目招生 · 最近核对 2026-10-24
- 详情核验
判定依据（原文摘录）
- is_phd
Type of degree Doctor of Philosophy
- english_ok
English language qualification (if applicable)
- bachelor_ok
A UK 2:1 honours degree, or its international equivalent.
原文
View all current projects
Postgraduate research project
Predictive energy management of battery packs
Funding
Competition funded
Competition funded
View fees and funding
Type of degree
Doctor of Philosophy
Entry requirements
2:1 honours degree
2:1 honours degree
View full entry requirements
Faculty graduate school
Faculty of Engineering and Physical Sciences
Closing date
30 Apr 2027
On this page
About the project
Potential supervisors
Entry requirements
Fees and funding
How to apply
Contact us
About the project
Potential supervisors
Entry requirements
Fees and funding
How to apply
Contact us
About the project
This project develops a predictive battery thermal management system for lithium-ion batteries, combining solid-state Peltier elements with a hybrid AI controller. A predictive model forecasts thermal loads; a decision algorithm optimises Peltier operation, minimising parasitic energy. Validated via MATLAB/Simulink simulation and experiments, it targets safer, longer-lasting, more efficient energy storage.
The performance, longevity, and safety of lithium-ion batteries, the cornerstone of electric vehicles and grid-scale energy storage, are critically dependent on maintaining a narrow optimal operating temperature range. Conventional Battery Thermal Management Systems (BTMS), typically based on complex liquid cooling, are reactive and consume significant parasitic energy, reducing overall system efficiency. This research project shifts thermal management from reactive to predictive to provide a more efficient and reliable solution.
This project will investigate a novel BTMS architecture that pairs solid-state thermoelectric Peltier elements with an advanced artificial intelligence (AI) control system. Peltier elements offer significant advantages, including high reliability, silent operation, and precise, bidirectional (heating and cooling) temperature control. Critically, they also offer rapid response rates compared to traditional fluid-based cooling systems.
The core of this project is the development of a hybrid AI controller designed to minimise the parasitic energy consumption of the Peltier-based BTMS, while also giving more accurate, real-time, thermal control of the battery cells. This controller will consist of two synergistic components:
• predictive, to forecast the battery's future thermal load based on real-time operational and environmental data
• decision, to proactively control the Peltier element. By using the predictive algorithms’ anticipated thermal needs, the decision algorithm will operate the Peltier element in its most efficient profile to pre-emptively manage temperature fluctuations of the battery cells.
The methodology involves developing a high-fidelity, multi-physics simulation environment in MATLAB/Simulink to model the coupled electrochemical-thermal dynamics of the battery cells and the thermoelectric properties of the Peltier element. This virtual testbed will be used to train and validate the AI controller across a range of dynamic drive cycles and environmental conditions. The performance of the final AI-driven system will be experimentally verified.
The anticipated contribution of this research is a validated framework for an intelligent, energy-efficient, and highly reliable solid-state BTMS. By demonstrating the viability of AI-controlled thermoelectric devices, this work aims to advance battery management technology, leading to safer, longer-lasting, and more efficient electrical energy storage systems.
You will be trained in Lithium ion Batteries and Thermoelectric devices as well as Matlab and Komsol simulations.
The School of Engineering is committed to promoting equality, diversity inclusivity as demonstrated by our Athena SWAN award. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break. The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees’ well-being and work-life balance. The University of Southampton is committed to sustainability and has been awarded the Platinum EcoAward.
Potential supervisors
Lead supervisor
Professor Richard Wills
Head of Department
Supervisors
Professor Iris Nandhakumar
Professor
Research interests
• Scanning Probe Microscopy
• Carbon nanotubes
• Nanoscale materials
Entry requirements
A UK 2:1 honours degree, or its international equivalent.
Fees and funding
We offer a range of funding opportunities for both UK and international students. Horizon Europe fee waivers automatically cover the difference between overseas and UK fees for qualifying students.
Competition-based Presidential Bursaries from the University cover the difference between overseas and UK fees for top-ranked applicants.
Competition-based studentships offered by our schools typically cover UK-level tuition fees and a stipend for living costs for top-ranked applicants.
Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered.
For more information, please visit our postgraduate research funding pages.
How to apply
Apply now
You need to:
• choose programme type (Research), 2027/28, Faculty of Engineering and Physical Sciences
• select Full time or Part time
• search for programme PhD Engineering & the Environment (7175)
• add name of the supervisor in section 2 of the application
Applications should include:
• your CV (resumé)
• 2 academic references
• degree transcripts and certificates to date
• English language qualification (if applicable)
Contact us
Faculty of Engineering and Physical Sciences
For questions about applying, email our Doctoral College (doctoralcollege-admissions@soton.ac.uk).
Project leader
For an initial conversation, email Professor Richard Wills (rgaw@soton.ac.uk).