When it comes to battery modelling common engineering challenges are pre-sizing the battery pack, to account and control aging effects as well as thermal management. Luckily, Siemens offers a set of software and features that provides you with simulation capabilities from micro-structure electro-chemistry to cell, pack and system design.
Simcenter STAR-CCM+ battery simulation
One of the products in the portfolio comes in very useful even at different stages of the multi-scale battery modelling process. Simcenter STAR-CCM+ is not only a CFD-focused multi-physics software, it allows also to study effects of electrode morphology on the electrochemical performance at the micro-structure. Simcenter STAR-CCM+ with the Battery Simulation Module (BSM) allows you also to analyse complex battery systems. Electro-thermal simulation can be coupled with heat transfer and complex cooling flows and solved simultaneously. And eventually, Design Manager in Simcenter STAR-CCM+ can help you to optimize your battery pack for temperature uniformity and weight reduction.
Battery Design Studio
Battery Design Studio (BDS) is a virtual cell design platform. It lets you create a digital twin of a battery cell with great accuracy. The geometrical details and all components of the cell can be precisely defined. Coupling the geometry to advance performance models (Physics-based or Equivalent circuit models) provides the ability to simulate the cell performance under various conditions pulses or duty cycles.
AMESIM System Simulation
Finally, to study a full system like an electrified car, on a system level, Simcenter AMESIM can be used for realistic pre-design, accurate electrical and thermal estimation. At an early design stage with AMESIM you can study the impact of geometrical design and optimize package sizes. The Battery Pre-Sizing tool in AMESIM determines the dimensions, the mass, and the performances of a virtual electrochemical cell from commercial cells data of the same chemistry, for a specific target application.
However, AMESIM can also simulate the system behaviour during the whole battery life in only a matter of seconds. The example above shows for instance the system for an electrical car which will be charged following different strategies:
- End of mission profile
- Just in time
- Charge “when you can”
By simulating the weekly use of the car over a whole year, considering temperature changes during a day and over the year, AMESIM can predict the capacity loss of that battery pack. The graph below shows quite clear that charging Just in time gives the lowest losses for a Lithium NCA-C battery. In case this sounds interesting or if you have any questions regarding this or on any other topic, do not hesitate to reach out at firstname.lastname@example.org.