Lean burn engines are more fuel efficient than standard stoichiometric-burn engines but at the same time, the conventional three-way catalyst is not effective in reducing the NOx in oxygen-rich exhaust. One of the recent advancements in exhaust after treatment technologies for lean burn engines is the NOx storage and reduction (NSR) methodology. In this mechanism, NOx is stored on the storage component of a NSR catalyst during normal engine operation. However, before the catalyst reaches its saturation capacity, an excess of fuel is injected to the engine for a very short period resulting in reductant rich exhaust and during this period, NOx is released and subsequently reduced to N2, therefore, restoring the storage capacity of the catalyst. The operation is cyclic in nature, with the engine operating between an oxygen rich feed for long periods and a fuel rich feed for relatively shorter periods. To implement this technology in the most efficient way, a detailed understanding of the NSR chemistry under different operating conditions is required. For the past few years, several authors have studied the NSR systems using both experimental and modeling techniques. However, most of the models proposed in the literature were calibrated against the steady cyclic operation where the NOx profiles are similar for each cycle. In real life situations, the engine operation changes with different driving conditions, occurring due to sudden acceleration, roads in hilly areas, non-uniform braking, etc., which results in operation with a number of different transient cycle-to-cycle regimes depending upon the frequency with which the engine operation is altered. Due to such varying conditions, it is very important to investigate the significance of transients observed between the two different steady cycle-to-cycle operations for the optimization and control purposes. Also, the models in the literature are specific to the catalyst used in the study and therefore, their adaptation to other NSR catalysts is not straightforward. Therefore, one of the main motivations behind this research work is to develop a general approach to explain the storage dynamics. Moreover, the existing models have not studied the regeneration mechanisms, which is very important to explain the cyclic data in complete operation including both transients and steady state cycles.