Abstract:
Hybrid Electric Vehicles or HEVs are a potentially effective way to reduce fuel consumption, improve vehicle efficiency, and maintain the safety requirements associated with standard automobiles. A Power Management Strategy (A PMS), a crucial element that directly affects both gasoline consumption and overall performance, is essential to their effectiveness. This study has included rule-based optimisation methodologies as part of its quest to optimise HEV functioning. The main emphasis will be on a real-time HEV model, with careful consideration of details like engine output, battery dynamics, and motor configurations. In order to get started with this study, a computer model that closely resembled the real-time HEV was carefully built with the MATLAB Simulator. A thorough investigation of the vehicle’s operation in a variety of settings was made possible by this simulation. By utilising specified threshold values, the HEV’s engine was carefully regulated. Through the implementation of these optimised solutions, a significant milestone had been reached: a 13.45% reduction in fuel usage. This achievement is a significant step towards improving the vehicle’s efficiency that is consistent with the overall objective of reducing fuel consumption without compromising performance. The accomplishment of this research demonstrates the tremendous potential and applicability of rule-based optimisation in improving the efficiency and performance of hybrid cars. Tangible improvements in fuel economy have been achieved by utilising accurate threshold-based controls and combining advanced modelling tools like as MATLAB. This study’s consequences go beyond simple data; it suggests a workable strategy to reduce the negative effects of conventional fuel usage in automobiles on the environment and associated operational costs. Moreover, the methodical use of rule-based tactics highlights the viability of incorporating these methods into the HEV’s operating framework, paving up possibilities for further developments in transportation that uses less energy. This study demonstrates that rule-based optimisation techniques may effectively cut fuel usage without compromising the performance requirements for real vehciles. Future mobility solutions that are efficient and sustainable will be made possible by additional advancements and developments in HEV power management, which are set to completely transform the automobile industry as technology develops.
Aim and Objectives:
The aim of this study is to investigate and change supervisory control strategies tailored for parallel HV with the overarching goal of achieving enhanced fuel efficiency. Parallel HV, which leverage both internal combustion engines (ICE) and electric motors for propulsion, offer a unique platform for optimizing powertrain performance.
- To investigate strategies for smart power distribution among the electric motor& internal combustion engine, seeking to optimize fuel efficiency while maintaining top-notch vehicle performance.
- To create dynamic energy management algorithms to control the energy transfer among the fuel converter, electric motor, and battery energy storage system, ensuring effective use and reducing energy wastage.
- To investigate and implement regenerative braking strategies that capture and store energy during deceleration, subsequently utilizing this energy to recharge the battery, thereby improving overall energy efficiency.
- To devise control strategies that dynamically adjust to real-time driving conditions, load variations, and battery state of charge, ensuring optimal performance under diverse operational scenarios.
- To deploy strategies focused on reducing fuel usage across various driving situations, including urban commuting and highway travel, while considering variables like traffic flow and road conditions.
- To focus on maintaining or enhancing vehicle drivability and performance while concurrently achieving fuel efficiency targets, ensuring a positive and seamless driving experience for end-users.
Fig: rule applied to MATLAB function
Fig: Fuel consumption or with and without rules
Fig: power developed by the engine and motor for with and without rules
Fig: shaft speed with and without rules