Particle Swarm Optimization Tuned Sliding Mode Control of Switched Reluctance Motor for EV Application
| dc.contributor.advisor | Mengesha, Mamo (PhD) | |
| dc.contributor.author | Aschalew, Nigussie | |
| dc.date.accessioned | 2022-02-02T11:06:54Z | |
| dc.date.accessioned | 2023-11-28T14:20:37Z | |
| dc.date.available | 2022-02-02T11:06:54Z | |
| dc.date.available | 2023-11-28T14:20:37Z | |
| dc.date.issued | 2022-01 | |
| dc.description.abstract | In this thesis, a sliding mode speed controller along with the particle swarm optimization algorithm and discrete commutation logic of switched reluctance motor is presented. The switched reluctance motor has several interesting advantages. For instance, the switched reluctance motor has high starting torque, a wide speed range, heat-tolerant capability, and a simple braking mechanism, which make it attractive for electric vehicles (EVs) traction applications. The switched reluctance motor has high torque ripples which affect the performance of the motor, and it is a highly nonlinear plant due to the doubly salient structure. A performance comparison of conventional proportional integral speed controller with sliding mode speed controller is presented for the 10/8 Switched Reluctance Motors. A robust controller is advised for high-performance control of switched reluctance motors. The effectiveness of the sliding mode controller for the SRM is confirmed by simulation results. The proposed controller guarantees that the actual motor speed tracks the reference speed slightly faster than the proportional-integral controller. The speed difference between the actual and the reference for a PI speed controller is 0.18% while for the SMC is 0.0002% which implies the PI has larger steady state error. The robustness of the proposed controller to sudden disturbances is also validated through simulation studies. The sliding mode speed controller parameters are obtained with the help of the Particle Swarm Optimization (PSO) algorithm while the PI speed controller gains are obtained using trial and error. The performance of the loaded Switched Reluctance Motor (SRM) is tested and evaluated with the help of simulation. The vehicle is modeled in MATLAB/SIMULINK and developing the torque-speed characteristics that represent the vehicle load type. The SRM reached its steady-state velocity of 570.74RPM in 13sec and also it took 4.5sec to stop the vehicle from running at a steady-state speed. | en_US |
| dc.identifier.uri | http://etd.aau.edu.et/handle/12345678/29845 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Addis Ababa University | en_US |
| dc.subject | Switched Reluctance Motor | en_US |
| dc.subject | Electric vehicle | en_US |
| dc.subject | PSO | en_US |
| dc.subject | Sliding Mode Controller. | en_US |
| dc.title | Particle Swarm Optimization Tuned Sliding Mode Control of Switched Reluctance Motor for EV Application | en_US |
| dc.type | Thesis | en_US |