Nitrogen oxide (NOx) sensing is required both for on-board diagnosis and optimal selective catalytic reduction (SCR)- catalyst control in heavy duty diesel engines. This can be accomplished either by physical solid-state sensors, or by so-called virtual sensors, which estimate the value of the target quantity using other states by means of a model. Both approaches have advantages and disadvantages. This paper resumes the derivation and the identification of a virtual sensor based on a polynomial structure and optimal experimental design methods and compares its performance to the one of a production physical solid state sensor. The virtual sensor is compared with a commercially available solid-state sensor in terms of accuracy (stationary as well as dynamic) and operation limits. To this end both sensors were tested on several stationary and transient heavy duty test cycles like the European Stationary Cycle (ESC), the European Transient Cycle (ETC), the World Harmonized Stationary Cycle (WHSC) and the World Harmonized Transient Cycle (WHTC) and on further stationary measurement data to determine their behavior under relevant engine operating conditions. The analysis also included several special cases like driving cycles with increased exhaust-backpressures, warm-up phases of the sensors and different sensor mounting positions. © 2010 SAE International.