Optimising ship’s engines with the help of virtual sensors

In the world of global shipping, deep-sea vessels are the industry¡¯s workhorses, tirelessly transporting goods across the main maritime routes. Unfortunately, they are also heavy polluters: their giant engines tend to burn heavy fuel oil with a high sulphur content. Not only do they damage the environment, but their extremely high fuel consumption also blows a hole in the budgets of shipping companies. Fuel accounts up to 80 percent of the costs incurred over the life of a deep-sea vessel, compared with below 20 percent for a typical car model.

Tougher legislation on emissions is also making life more difficult for deep-sea vessels. Especially when sailing in coastal waters, the big cargo ships and cruise liners have to meet far stricter emission levels than in the past. Shipping companies are therefore keen to optimise their ship engines in a way that keeps fuel costs as low as possible, despite tougher emission controls.

Inefficient tuning

Through their ETH spin-off Vir2sense, researchers Christophe Barro and Panagiotis Kyrtatos offer an innovative solution for optimising marine engines. During their research over the past eight years, the two mechanical engineers have developed combustion and emission models that can be used as virtual sensors in a physical engine. Their plan is to use these sensors in a commercial environment to simulate the performance of large ship engines. These models are then used for continuous re-tuning of the engines for specific emission limits and minimization of fuel consumption independently from current environmental and operating conditions. This becomes increasingly important when taking into account different fuel qualities, which can change the engine combustion behaviour and emissions significantly.

Depending on the price of fuel and transport volumes, ships can change their nominal speed in order to save fuel and reduce emissions. In some cases, ship owners swap out individual components to make the engine run more efficiently at lower speeds. This task is generally performed mostly on the basis of empirical values. ¡°Tuning an engine can be a little hit and miss; it can require significant time which cannot be used to transport goods and can result in high fuel and other operating costs ¨C a model-based approach produces a far more efficient result¡±, explains Barro.

Virtual sensors bring a massive improvement

With the help of their virtual testbed, Barro and Kyrtatos are able to calculate in advance on the computer how a motor will run with certain settings and which of its components need to be modified ¨C and how ¨C in order to achieve the necessary savings.

The researchers use virtual sensors to ¡°measure¡± the engine¡¯s emissions, among other things. These sensors have a big advantage over their physical counterparts: they can be placed anywhere in the engine. Physical sensors, on the other hand, can only be placed in a limited number of positions. ¡°If you want to monitor the engine of a giant cargo ship, for example, you can¡¯t simply stick a sensor in the exhaust pipe in order to measure emissions¡±, Barro stresses. The physical environment in the exhaust system of a marine engine is very harsh, and physical sensors have to be replaced sometimes after less than 100 hours of operation. The average deep-sea vessel travels around 8,000 hours a year, however. On top of that, the sensors have to be recalibrated after a short period, which is time-consuming and expensive.