Modern automotive gasoline engines have highly efficient after-treatment systems that reduce exhaust gas emissions. However, this efficiency greatly depends on the conditions of the exhaust gas, mainly the temperature and air–fuel ratio. The temperature instability during transient conditions may cause a reduction in the efficiency of the three-way catalyst (TWC). By using a thermal energy storage system before TWC, this negative effect can be suppressed. In this paper, the effects of the temperature stabilization on the efficiency of the three-way catalyst were investigated on a 1-D turbocharged gasoline engine model, with a focus on fuel consumption and emissions. The thermal energy storage system (TESS) was based on PCM materials and was built in the exhaust between the turbine and TWC to use the energy of the exhaust gas. Three different materials were picked up as possible mediums in the storage system. Based on the results, the usage of a TESS in a gasoline after-treatment system has shown great potential in improving TWC efficiency. This approach can assist the catalyst to operate under optimal conditions during the drive. In this study, it was found that facilitating the heat transfer between the PCM and the catalyst can significantly improve the emissions’ reduction performance by avoiding the catalyst to light out after the cold start. The TESS with PCM H430 proved to reduce the cumulative CO and HC emissions by 8.2% and 10.6%, respectively, during the drive. Although a TES system increases the after-treatment cost, it can result in emission reductions and fuel consumption over the vehicle’s operating life.

This study focuses on the use of eye-tracking technology to analyse the rider’s visual attention during racing on a Ducati Panigale V2 motorcycle. Using the TOBII Pro Glasses 2 system, the rider’s gaze dynamics were recorded, including fixations, eye movements (saccades) and gaze distribution on key sections of the track. The results revealed a link between gaze stability and cornering efficiency, particularly in optimising braking points and selecting the ideal trajectory. Identifying unstable visual behavior—such as frequent gaze deviations or constant switching between reference points—provides valuable insights for improving driving technique. This approach confirms the importance of eye-tracking as a tool for objective evaluation and optimization of rider performance in motorsport.

A micro cogeneration unit based on a three-cylinder internal combustion engine, Skoda MPI 1.0 L compressed natural gas (CNG), with an output of 25 kW at 3000 RPM is proposed in this paper. It is a relatively simple engine, which is already adopted by the manufacturer to operate on CNG. The engine life and design correspond to the original purpose of use in the vehicle. A detailed dynamic model was created in the GT-SUITE environment and implemented into an energy balance model that includes its internal combustion engine, heat exchangers, generator, battery storage, and water storage tank. The 1D internal combustion engine model provides us with information on engine start-up time, actual effective power, friction power, and the amount of heat going to the cooling system and exhaust pipe. The catalytic converter was removed from the exhaust pipe, and the engine was always operating at full load; thus, engine power control is not considered. An energy storage system for an island operation of the entire power unit for a large, detached house was designed to withstand accumulated energy for a few days in the case of a breakout. To reach a low initial system cost, the possible implementation of worn-out battery packs toward emission reduction in terms of the second life of the battery is proposed. The energy and emission balance are carried out, and the service life of the engine is also discussed.

This study presents a novel method for the rapid identification of key performance indicators (KPIs) from measured riding data of a Ducati Panigale V2 motorcycle, aimed at enhancing racing performance through a deeper understanding of rider-vehicle interaction. The methodology involves the design and implementation of mathematical tools within the RaceStudio3 software to analyze data from the motorcycle’s sensor system. This approach facilitates the swift detection of critical events, including gearshift delays, improper throttle control, and suspension issues. The fusion of data from the motorcycle enables a comprehensive evaluation of the rider’s influence on performance. The results demonstrate the potential of the proposed method to provide valuable insights for optimizing motorcycle setup and rider technique.