For use with the MathWorks Matlab and Simulink platform, NXP Semiconductors has created a Model-Based Design Toolbox (MBDT) for Battery Management Systems (BMS).
The MBDT for BMS is said to streamline model-based design for intelligent battery health management by making it easier to develop, test, and implement BMS algorithms on NXP processors.
Because it guarantees the best possible performance, longevity, and safety of the battery packs that drive these cutting-edge cars, the BMS is essential for EVs.
In order to fine-tune algorithms unique to the battery cell types and battery pack layout of EVs, the BMS design process is increasingly depending on modeling and simulation.
The BMS algorithms may be efficiently designed thanks to model-based design, which also makes it possible to simulate and test them for many scenarios, including driving patterns, environmental factors, and fault occurrences.
Engineers may easily move straight from Matlab and Simulink models to executing and testing BMS algorithms on an NXP processor with MBDT for BMS. This feature speeds up the testing and prototype stages and streamlines the BMS development process.
The MBDT for BMS fills the gap between design theory and real-world implementation. To maintain the efficiency and integrity of the original algorithms, engineers can simply implement their Simulink BMS models onto NXP processors without the need for human coding.
Furthermore, engineers may conduct dynamic, real-world testing on their BMS systems with the help of the MBDT BMS product’s integrated input/output (IO) connectivity, which offers instant feedback from early hardware prototypes and insights into system performance under varied conditions.
For BMS solutions to be safe and reliable in practical situations, this degree of testing is essential.
Key Comments
“Simplifying direct testing with MBDT on NXP processors offers a broad range of benefits, including faster design iterations that allow engineers to identify and fix issues upfront in the design process and reduce time to market,” said Lars Reger, CTO of NXP.
“By enabling engineers to go directly from creating BMS algorithms in Simulink to running them on an NXP processor, we’re simplifying and accelerating the development process,” said Jim Tung, MathWorks Fellow. “The growth of the EV market demands more efficient, reliable, and safer battery systems, and tools like MBDT that streamline and enhance the engineering process will be critical. Reducing development times, facilitating easier testing, and accelerating market entry will be differentiators in this competitive market.”
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