Secondmind for Calibration
Virtualize physical testing and efficiently identify optimum calibration parameters, improving performance and reducing test bench time to accelerate development cycles.
Secondmind for Calibration takes a novel approach to model-based calibration using machine learning techniques to intelligently automate DoE and streamline data acquisition. This means less data is required to generate accurate calibration maps, significantly reducing the time it takes to fully calibrate systems.
Benefits
Achieve optimum calibration profiles in 50% less time and reduce prototypes by 40% with Secondmind for Calibration
How Calibration works
Our Calibration software connects to existing calibration toolchains and runs Secondmind Active Learning on the latest GPUs in the cloud. The calibration engineer provides a small amount of 'seed' data that allows Secondmind Active Learning to build an initial model based on the engineer’s requirements. Secondmind's intelligent automation begins.
Secondmind Active Learning determines the optimal experiment to run and requests data from the test bench. Once the test bench returns data, the model is updated and analyzed against the constraints and the algorithms intelligently design the next experiment. This cycle automatically repeats until enough data has been collected to build an accurate calibration map, requiring far fewer experiments than traditional model-based DoE processes.
Impact
Secondmind for Calibration speeds up calibration processes by automatically and intelligently identifying the most valuable data points to uncover the best calibration settings for optimal performance, lower emissions, and longer battery range.
80%
reduction in data requirements
50%
faster calibration cycles
40%
reduction in prototype costs
80%
reduction in test bench usage
Use cases
E-powertrain calibration
Precisely finetune parameters of the battery, inverter, power electronics and motors to strike the optimum balance between maximum performance and overall efficiency of electric powertrains.
Battery management calibration
Develop accurate calibration maps that optimize the charge and discharge profiles of the cells, improving energy efficiency, thermal behaviour and extending cycle life
Hybrid system calibration
Optimize the calibration of ICE and e-motor, integrating control strategies for fuel delivery, ignition timing, and electric assistance to achieve peak performance and efficiency in hybrid powertrain systems.
Applications
Secondmind for Calibration has been pioneered to accelerate the calibration of a wide variety of automotive R&D applications, including:
E-motor
Internal combustion engines
Hybrid and electric powertrains
Battery management
Hydrogen fuel cells
Steering
Transmission
Key features
Intelligent, automated DoE
Accelerate workflows with Secondmind’s intelligent automated DoE system
Get started quickly with minimal or no data.
Streamline DoE using 80% less data than conventional methods.
Eliminate time consuming manual experiment design.
Advanced modeling
Leverage advanced machine learning models to build reliable and accurate calibration maps
Physics-informed models to increase accuracy and further reduce data requirements
Manage noise to robustly and accurately interpret test data
Capture complex interactions and non-linear behaviour
Critical parameter optimizer
Refine essential system parameters whilst considering an array of user-defined constraints
Optimize any given objective, ensuring precision and efficiency by considering all relevant constraints and parameters.
Experiment with novel parameter combinations to uncover innovative solutions.
Enable precise tuning even in complex, multi-variable environments.
Core capabilities
Our easy-to-use cloud-based software products are built for engineers and offer a
safe and secure environment to accelerate productivity:
Learn more
Learn from our customers and team how Secondmind for Calibration reduces data requirements and minimizes testbench usage.
