Plug-in Hybrid Electric Recreactional Boat (PHERB) is a new innovation of conventional boat for water transportation. In the PHERB powertrain, the main power source to drive the boat is the electric machine (EM). The primary energy source of EM is the battery. Battery is an important power energy supplier to PHERB and has two main conditions such as charging and discharging conditions. In this paper, the optimal design of the battery in a discharging condition is reported. The battery model is developed in MATLAB/Simulink environment together with a closed-loop feedback PI controller. By using a power demand curve as a reference for the model, the optimal performance of the discharging battery is obtained by using the genetic algorithm optimization. The results of optimal control parameters of the system are compared with the trial-and-error method. It has been found that the proposed optimal system design can improve the discharged battery's performance significantly.
Driving cycle is essential for researchers and also vehicle developers to study the performance of the vehicle mainly via simulations. However, the driving cycles are not the same for different countries or cities, although they may seem identical. In this paper, several driving cycle data were collected for different routes in Kuala Terengganu city at peak hours which were then split into several micro-trips. A genetic algorithm was used as a procedure for selecting the optimised micro-trip to develop a complete Kuala Terengganu driving cycle. Then, the proposed driving cycle was compared with other existing driving cycles such as Urban Dynamometer Driving Schedule, Highway Fuel Economy Test Cycle, Supplemental Federal Test Procedure and Environmental Protection Agency. The proposed complete Kuala Terengganu driving cycle was successfully developed with 10 micro-trips and a total time of 1600s. The results showed that the comparison of percentages error for characteristic parameters for the KT and UDDS driving cycle was the lowest at 161.4 percent compared to others. This indicated that KT driving cycle and UDDS driving cycle is similar to each other as the driving cycle for cities. As a conclusion, the KT driving cycle was successfully obtained using the GA method with all of the percentage error for all parameters of below 10 percent, except for the percentage of cruise time. The results for the comparison also proved that the KT driving cycle is similar to UDDS driving cycle where both are the driving cycle for cities.
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