On cold start operation of an SI engine, a catalyst shows poor performance before it reaches activation temperature. Therefore, fast warmup of the catalyst is very crucial to reduce harmful emissions. In this study, an appropriate control strategy is investigated to increase exhaust gas temperature through changes of spark timing. Combustion stability is also considered at the same time. Exhaust gas temperature and pressure of combustion chamber are measured to investigate the effects of spark timings on cold start and idle performance. Experiments showed that retarded spark timing promotes the combustion at the end of expansion stroke and increases exhaust gas temperature during cold start.

On cold start operation of an SI engine, a catalyst shows poor performance before it reaches activation temperature. Therefore, fast warmup of the catalyst is very crucial to reduce harmful emissions. In this study, an appropriate control strategy is investigated to increase exhaust gas temperature through changes of spark timing and exhaust valve timing. Combustion stability is also considered at the same time. Experiments showed that retarded spark timing promotes the combustion at the end of expansion stroke and increases exhaust gas temperature during cold start.An advance of exhaust valve timing decreases residual gas in cylinders due to decrease of valve overlap period. It helps improvement combustion stability by virtue of reduced residual gas. A control strategy of proper valve timing and spark timing is suggested in order to achieve fast light-off of the catalyst and stable operation of the engine in a cold start and idle operation

The main goal of e-learning systems is just-in-time knowledge acquisition. Rule-based elearning systems, however, suffer from the mesa effect and the cold start problem, which both result in low user acceptance. E-learning systems suffer a further drawback in rendering the implementation of a natural interface in humanoids difficult. To address these concerns, even exceptional questions of the learner must be answerable. This paper aims to propose a method that can understand the learner’s verbal cues and then intelligently explore additional domains of knowledge based on crowd data sources such as Wikipedia and social media, ultimately allowing for better answers in real-time. A prototype system was implemented using the NAO platform.