Adaptive cruise control electric vehicles is a B.Tech project topic for Instrumentation and Control Engineering. It gives students a clear starting point for research, implementation planning, and documentation.
Adaptive cruise control electric vehicles Project Details
| Abstract |
As electric mobility becomes more commonplace, the need for additional safety features, including Advanced Driver Assistance Systems (ADAS), is essential for safety and reducing the risk of human error. A primary concern is the development and implementation of effective control systems, especially with respect to the intricate structure and the power distribution of electric drives. The purpose of this project is to investigate new approaches to Adaptive Cruise Control (ACC) for Electric Vehicles (EVs) designed for model parameter adjustment and online control layer optimization to be used through a single-platform approach. The focus of this method is an intelligent Model Predictive Control (MPC) strategy that utilizes a decentralized control approach
for each of cruising, gap keeping, and braking. A single, integrated predictive model is used to generate real-time, look-ahead predictions of driving situations, utilizing data acquired from various sensors. Experimental tests are required to determine the effectiveness of the proposed predictive model and the dynamic switching of control modes. Testing is done using a real EV that is equipped with a chassis dynamometer, where a lead vehicle is emulated and detected using an onboard LiDAR sensor to demonstrate an integrated control method.
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| Reference Paper |
Adaptive cruise control for electric vehicles using hybrid-mode MPC |
| Domain |
Instrumentation and Control Engineering |
| Sub-Domain |
Control System Design |
| PDF Download |
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| Get Help |
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