Model Predictive Coolant Allocation for Integrated Tab Surface Cooling of Battery Cells

Q: What problem does integrated tab-surface cooling (ITSC) address?

It addresses the limitation of using tab cooling or surface cooling alone, which restricts the trade-off between reducing thermal gradients and limiting temperature rise. ITSC combines both by allocating coolant dynamically across the tab and lateral surfaces.

Q: How is coolant allocation formulated and solved in the proposed approach?

Coolant allocation is formulated as an optimal control problem that regulates battery temperature toward a desired reference while minimizing thermal gradients. It is solved using a computationally efficient real-time iteration model predictive control (RTI-MPC) scheme.

Q: What performance benefits are reported for RTI-MPC compared with nonlinear MPC?

Under realistic driving conditions, RTI-MPC reproduces nonlinear MPC thermal response with absolute errors below 0.0035°C, while reducing computation time from several seconds to 19.3 ms. This supports potential real-time implementation.

Jul 16, 2026

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Battery tab cooling reduces internal thermal gradients by leveraging the high conductivity of current collectors, while surface cooling suppresses overall temperature rise through a large heat-transfer area. Using either approach alone limits the attainable balance between uniformity and temperature reduction. The proposed integrated tab-surface cooling (ITSC) dynamically allocates coolant between lateral surface and tab channels, formulated as an optimal control problem that tracks a temperature reference and minimizes thermal gradients. A first-principles coolant model is combined with battery and valve-actuation models. Real-time iteration MPC achieves nonlinear benchmarks with <0.0035°C absolute error and cuts computation to 19.3 ms.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages14

Reading Time35 min

Abstract

Introduction

Battery thermal management background

Passive vs active BTMS approaches

Lateral surface cooling vs tab cooling

Cooling-interface design considerations

Model Predictive Coolant Allocation for Integrated Tab–Surface Cooling of Battery Cells Godwin K Peprah, Student Member, IEEE, Torsten Wik, Member, IEEE, Masood Tamadondar, and Changfu Zou, Senior Member, IEEE arXiv :2607 . 10872v1 [ ee ss . SY] 12 Jul 2026 Abstract—Battery electrical tab cooling is effective at reducing internal thermal gradients by exploiting the high thermal conductivity of the current collectors, whereas surface cooling is effective at reducing temperature rise because of its large heat transfer area. Using either strategy alone, however, limits the achievable trade-off between thermal uniformity and temperature rise reduction. This work proposes an integrated tab-surface cooling (ITSC) system in which coolant is dynamically allocated among the lateral surface and tab channels. The allocation is formulated as an optimal control problem in which the battery temperature is regulated towards a desired reference and thermal gradients are minimised. To support this formulation, a first-principles coolant model is developed and coupled with battery and valve-actuation models. The resulting optimal coolant-allocation problem is solved using a computationally efficient real-time iteration model predictive control (RTI-MPC) scheme, with a nonlinear MPC serving as a closed-loop performance benchmark. Evaluation results under realistic driving conditions showed that RTI-MPC reproduces the nonlinear MPC thermal response with absolute errors below 0.0035 ◦ C while reducing the computational cost from several seconds to 19.3 ms, indicating strong potential for real-time implementation. Additionally, evaluation of the proposed ITSC system against conventional cooling configurations demonstrates that ITSC achieves the best overall trade-off between temperature regulation and thermal gradient reduction. Index Terms—Battery thermal management, real-time model predictive control, tab and surface cooling, electrothermal battery modelling, coolant flow modelling, coolant allocation control. I. INTRODUCTION THANKS to their long extended cycle life, high energy and power density compared to other rechargeable batteries, Lithium (Li)-ion batteries are the dominant energy storage technology for numerous applications, including electric vehicles (EVs), stationary energy storage systems, and portable electronics [1] . Despite these advantages, their safety, power and energy capability, charge acceptance, and lifespan are strongly dependent on temperature [2] . Operating at elevated temperatures accelerates irreversible degradation and increases the risk of thermal runaway, while large temperature differences within a cell, known as thermal gradients, could This work was funded in part by the Swedish Research Council (Grant No. 2023-04314) and the Swedish Energy Agency through the Swedish Electromobility Centre (Grant No. 13011) . Godwin K. Peprah, Torsten Wik, and Changfu Zou are with the Department of Electrical Engineering, Chalmers University of Technology, 41296 Gothenburg, Sweden (e-mail: [godwinp@chalmers.se](godwinp@chalmers.se); [tw@chalmers.se](tw@chalmers.se); [changfu.zou@chalmers.se](changfu.zou@chalmers.se)). Masood Tamadondar is with the Energy Storage System and Electromobility Department, Volvo Group Trucks Technology, BF32420 CampX Gothenburg, Sweden ([e-mail: masood.tamadondar@volvo.com](e-mail: masood.tamadondar@volvo.com)). lead to uneven ageing and localised mechanical stress within the electrodes [2], [3] . Consequently, a sophisticated battery thermal management system (BTMS) [4] is not only beneficial but essential for ensuring safe, long service life, and reliable operation of these batteries. BTMS can be broadly categorised as passive or active. Passive systems rely on natural heat dissipation mechanisms, whereas active systems employ auxiliary devices such as fans or pumps to enhance heat transfer. Established BTMS include air cooling, liquid cooling, phase-change materials, and i

FAQs

What problem does integrated tab-surface cooling (ITSC) address?

It addresses the limitation of using tab cooling or surface cooling alone, which restricts the trade-off between reducing thermal gradients and limiting temperature rise. ITSC combines both by allocating coolant dynamically across the tab and lateral surfaces.

How is coolant allocation formulated and solved in the proposed approach?

Coolant allocation is formulated as an optimal control problem that regulates battery temperature toward a desired reference while minimizing thermal gradients. It is solved using a computationally efficient real-time iteration model predictive control (RTI-MPC) scheme.

What performance benefits are reported for RTI-MPC compared with nonlinear MPC?

Under realistic driving conditions, RTI-MPC reproduces nonlinear MPC thermal response with absolute errors below 0.0035°C, while reducing computation time from several seconds to 19.3 ms. This supports potential real-time implementation.

Jul 16, 2026

Upload by Sage