Thermal management in an electric vehicle is important to extend the life of the battery. This paper is about modelling and analysis of a 6-kW battery module for improving the thermal performance of the lithium ion battery in electric vehicles with PCMs (phase change materials). For a battery thermal management system, we considered phase change materials such as RT15 (Rubitherm15), RT31, EG5 (Expanded Graphite5), and EG26 PCMs with different thermal properties. The ambient temperature conditions range considered was over 40 °C and below −10 °C, also tested on the hot and cool soaking conditions. The lithium polymer pouch single battery was designed and simulation analysis was performed with and without PCMs to enhance heat transfer rate. The simulation and experiment results on a single battery were satisfied to control the battery temperature within the safe operating conditions. Hence the proposed battery thermal management system (BTMS) was applied on a 6-kW battery pack. The design of the battery module was done in AUTOCAD and analysis was done in ANSYS CFD (computational fluid dynamics) software tool.

Recent studies on autonomous vehicles focus on improving driving efficiency and ignore driving comfort. Because acceleration and jerk affect driving comfort, we propose a comfort regenerative braking system (CRBS) that uses artificial neural networks as a vehicle-control strategy for braking conditions. An autonomous vehicle driving comfort is mainly determined by the control algorithm of the vehicle. If the passenger’s comfort is initially predicted based on acceleration and deceleration limits, the control strategy algorithm can be adjusted, which would be helpful to improve ride comfort in autonomous vehicles. We implement numerical analysis of the control strategy, ensuring reduced jerk conditions. In addition, backward propagation was applied to estimate the braking force limits of the regenerative braking systems more accurately. The developed algorithm was verified through the Car Sim and MATLAB/Simulink simulations by comparing them with the conventional braking system. The proposed CRBS offers effective regenerative braking within limits and ensures increased driving comfort to passengers.

This paper is about the control of robotic fish movement in an aquarium via human hand gestures detected by image sensors attached in the aquarium. In this study, sensors actively interact with humans and robotic fish. Image and radio frequency sensors are used to identify the position and color of robotic fish. Recently, we have studied human interactive control based on hand gesture recognition. Image sensors send the input signals of hand gestures obtained from real-time video images processed using tracking control algorithms, such as color mark, stop zone, and lead-lag tracking algorithms, to robotic fish. The movement of robotic fish is controlled via the movement of the two hands, where the left hand is for the fish to be controlled and the right hand is for controlling the movement of the robotic fish. Hand gesture recognition consists of hand feature segmentation and gesture recognition from the hand features. Our results show that interactive human control using hand gestures successfully controls the movement of robotic fish.

This paper is about the realization of robot fish motion along with 3D hologram fish in an aquarium, with the augmented reality of 3D aqua holograms to attract viewers. In this new proposed concept, the animated fish video with 3D hologram is projected into a robot fish aquarium. However, this process of projecting 3D hologram fish into a robot fish aquarium may cause the overlap of the robot fish with the animated fish. To avoid this problem of overlapping, sensors play an important role. Image sensors track the robot fish movement. The proposed concept can be realized by boundary detection and optical flow algorithms, which are used to detect the positions of the robot fish. The performance of this detection algorithm was evaluated and satisfactory results were obtained. This 3D hologram with augmented reality has been successfully installed at

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