Background in powertrain calibration required; basic knowledge of MATLAB recommended.
This hands-on, two-day course focuses on tools and techniques for using Design of Experiments, statistical modeling, and optimization to calibrate modern powertrain systems in MATLAB® and Simulink®. The course is designed for engineers who intend to calibrate and test engines, develop control algorithms, and simulate powertrain behavior. By the end of the course, attendees will be able to produce a set of optimal base calibration tables for a typical modern gasoline or diesel engine. Two subject variants, based on gasoline or diesel materials, are available. Topics include:
Working with Design of Experiments
-Setting up test plans
-Designing for constraints
-Applying classical, space-filling, and optimal methods
Data loading and handling
-Loading, visualizing, filtering, and augmenting measured data
Response surface modeling
-Creating one-stage and two-stage response-surface models using radial basis functions, polynomials, splines, and neural nets
-Setting up optimization problems
-Reviewing, executing, filling, and exporting tables
-Applying application-specific, multiobjective, and drive-cycle optimization
See if you are eligible for discounted pricing for academic users.
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