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            <title xml:lang="en">Real-time Simulation of Optimal Differential Flatness Based Energy Management Strategy for Electric Vehicle Applications</title>
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            <idno type="halRefHtml">&lt;i&gt;National Conference on Intelligent Energy Management and control of Renewable Energy Systems (NCIEMCRES'24)&lt;/i&gt;, Oct 2024, Bejaia, Algeria</idno>
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              <p>The proposal combines optimal energy management for electric vehicles via slap swarm optimization and differential flatness control. A battery-supercapacitor power system is utilized. A synchronous reluctance motor (SynRM) drive gets power from DC-DC bidirectional converters that connect each source in parallel to the DC bus. The suggested EMS basic forces utilize a combination of the complementing properties of two methodologies: the Slap Swarm Optimization Algorithm and Differential Flatness (DF). The Slap Swarm optimization algorithm employs a rapid optimization process to adapt the DF gains in real-time, hence enhancing system performance. DF employs predetermined trajectories that adhere to the system's physical properties, serving as an effective mechanism to ensure the dynamic restrictions of the sources while achieving the necessary robust control characteristics. A lot of hardware-in-the-loop (HIL) real-time simulations of the electric vehicle were run using the OPAL-RT OP4510 simulator to test the proposed EMS's viability and performance. The main goal of the suggested EMS is to keep the DC-bus stable by reducing the DC-bus voltage changes (Δv = 5 V) and voltage overshoots to 15 V (3.2%), while still meeting the SynRM motor's power needs. Moreover, the technique reduces induced harmonics from the drive (10.49%), decreasing the battery current ripple by 17.15A and thus improving the battery's lifespan.</p>
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