TY - JOUR
TI - A neuro-fuzzy based combustion sensor for the control of optimal engine combustion efficiency
AU - Miljić Nenad L
AU - Tomić Miroljub V
JN - Thermal Science
PY - 2013
VL - 17
IS - 1
SP - 135
EP - 151
PT - Article
AB - Modern and advanced control systems for internal combustion engines require  accurate feedback information from the combustion chamber. Whereas the  in-cylinder pressure sensor provides this information through its close  thermodynamic ties with the combustion process, drawbacks in its  implementation push research towards other nonintrusive sensing methods. This  paper suggests alternative methods of combustion phasing detection relying on  measured angular crankshaft speed. Method developed, achieves sensing of  angular position of the 50% of mass fraction burned (MFB50) through two  steps: calculation of, so called, synthetic torque and its nonlinear  transformation to a combustion feature estimator through local linear  Neuro-fuzzy based model (LLNFM). In order to calibrate both parts of this  virtual combustion sensor, parameters of a high-fidelity crankshaft dynamic  model are identified, and LLNF model is trained with extensive experimentally  collected data set. Created virtual MFB50 sensor, demonstrated its  performance, on a large test data set comprised of 70% of gathered data.