The thermal management of batteries is one of the key challenges of electric mobility in the automotive sector. Lithium-Ion batteries as well as other common battery types operate best in a certain temperature range, as the energy capacity drops outside of the range. Furthermore, aging effects can occur, reducing the battery lifetime. Therefore, a thermal management system is part of the battery pack. Battery cooling plates with integrated channel structure that are passed by a fluid for indirect liquid cooling by forced convection are a common realization of such systems. One of the most innovative and promising technologies for the efficient production of such plates is Rollbonding. The technology is characterized by competitive cost, great design freedom, and flexibility, as it enables the production of channel patterns without the need for a dedicated forming tool for every design. Designing battery cooling plates is challenging because conflicting thermal and hydraulic targets must be considered while ensuring manufacturability. Topology optimization is a well-known technology that can help designing optimal structures. One of the major challenges of topology optimization is the generation of designs that are feasible for the dedicated manufacturing technology. This paper addresses this issue by presenting an optimization strategy that considers the relevant manufacturing constraints based on machine learning models. These models are trained based on simulation data such that parameters like maximum material thinning and minimum channel height can be predicted and consequently considered within the optimization. Furthermore, a 3D parametrization strategy is presented that enables the representation of realistic 3D channel shapes as they result from the manufacturing process. This way, the hydraulic and thermal performance can be predicted with better accuracy compared to classical 2D methods.

Electric mobility depends on batteries, which typically require a thermal management system. Those systems are often realized as sheet metal plates with integrated channel structures. Rollbonding technology is one of the most promising technologies to produce such cooling plates due to the competitive cost structure in combination with its unmatched design freedom. However, the design of a cooling plate manufactured using rollbonding is challenging. Such a design requires thermal and hydraulic targets to be considered while manufacturing constraints must be satisfied. Due to the given design freedom and the conflicting targets manual design of cooling plates is challenging and requires significant development time and effort. Topology optimization is a popular method for automated and optimal design of components. In this paper, the authors present a strategy to design rollbonded cooling plates by topology optimization, taking thermal, hydraulic, and manufacturing requirements into account. State-of-the-art methods usually consider channel shapes with rectangular cross-sections, ignoring the effects of realistically curved channel cross-sections as they result from the manufacturing technology. The authors present a novel parametrization strategy, considering the 3D channel shape in a realistic manner. The mathematical formulation of the novel modelling approach is shown and validated based on a small, simplified test case. The methodology is implemented into a custom, solver-agnostic framework and coupled with commercial Finite Element software.

The transition of the automotive industry towards electro-mobility is highly dependent on the performance of batteries. Those batteries need a temperature management system, often realized as sheet metal cold plates with integrated channel structures for liquid cooling. Rollbonding technology is one of the most promising methods for industrial mass production of battery cooling systems in the automotive industry due to its competitive cost for low and high-volume applications and its great degree of design freedom. Designing cold plates is a challenging task due to conflicting thermal and hydraulic objectives, manufacturing requirements and the enormous design freedom offered by the rollbondig technology. Topology optimization is a well-known method for optimal design in multi-physics problems, such as cold plate design. Using a thermofluid topology optimization, the optimum channel patterns in a given design space can be found. However, the industrial application of such a design approach is challenging, as well-established topology optimization software often is designed for a wide variety of applications and, therefore, lacks manufacturing constraints and parametrization strategies feasible for the specific production process. This paper demonstrates how well-known parametrization and optimization strategies can be combined and adapted to generate topologies feasible for the manufacturing of cold plates by rollbonding. The integration of commercial solvers into an external, solver agnostic framework, considering custom manufacturing, continuation and filtering strategies is demonstrated. A density-based topology optimization is applied to the linear potential Darcy flow model, considering length scale constraints on the solid and fluid domain. A specific constraint is developed to assure the manufacturability of the design using the rollbonding technology. Further, a feasible continuation strategy considering projection parameters, penalization and length scale constraint activation and continuation is presented. The temperature distribution is optimized while considering pressure drop and manufacturing requirements. The topology optimization results are remodeled and validated using a high-fidelity RANS solver. The thermal-hydraulic performance is compared with a manually designed benchmark cold plate. Finally manufacturability of the outcomes is evaluated to prove the successful application of the proposed design technology.

Designing the layout of flow channels for forced convection is a complicated task as a compromise between hydraulic and thermal performance must be found and a wide variety of topology, shape, and size can be manufactured. The authors demonstrate the capability of Altair OptiStruct™ to create a basic layout by topology optimization. The flow analysis is based on the linear potential Darcy model to capture the incompressible steady-state flow. The flow resistance is modeled as porous media, which permeability distinguishes between the solid and fluid domain. The resulting velocity is used in the thermal convection–diffusion equation. In the thermal analysis, an additional discontinuity capturing term is discussed to prevent from numerical over- and undershooting of the temperature field. The optimization utilizes standard techniques like the density method, SIMP interpolation, robust approach, adjoint sensitivity analysis, and dual optimization. As application example, the cooling of automotive battery packs is shown. The cooling is realized by fluid flow through cooling channels manufactured by roll bonding. This manufacturing process allows for complex channel patterns, whereas the production cost is low compared to additive manufacturing or brazed cooling systems especially for high-volume applications. The temperature on the battery modules is optimized to have a uniformly low value, while keeping mechanical losses in the flow low.