Design and optimisation of a virtual prototype of a ground transportation system at very high-speeds in conditions close to vacuum
- Autores: Federico Lluesma Rodríguez
- Directores de la Tesis: Manuel Zaera Sanz (dir. tes.), Sergio Hoyas Calvo (dir. tes.)
- Lectura: En la Universitat Politècnica de València ( España ) en 2022
- Idioma: español
- Tribunal Calificador de la Tesis: Maria Belén García Mora (presid.), María Cruz Navarro Lérida (secret.), Manuel García Villalba Navaridas (voc.)
- Programa de doctorado: Programa de Doctorado en Diseño, Fabricación y Gestión de Proyectos Industriales por la Universitat Politècnica de València
- Materias:
- Enlaces
- Tesis en acceso abierto en: RiuNet
- Resumen
Hyperloop is considered the fifth means of transportation, after the car, boat, train and plane. It consists of a magnetically levitating capsule that travels within a tube in which the air pressure has been reduced. Thus, the ground friction and aerodynamic drag are minimised, reaching ultra high-speeds at ground level.
Several maglev trains and hyperloop concepts being developed currently. Most of them propose levitating using Electromagnetic Suspension (EMS). Zeleros, the company where this Thesis was done, has a similar approach. It employs a Hybrid EMS (HEMS)In particular, the Zeleros approach employs a Hybrid EMS (HEMS), combining permanent and electromagnets to reduce energy requirements. As for the propulsion, the approach is unique as it uses a compressor from the aeronautical industry. CFD simulations prove that using a compressor considerably reduces the aerodynamic drag in the closed environment, as the piston effect gets mitigated. For the same tube size and pressure, a hyperloop with compressor requires up to 70 % less power. In other terms, if the same power is installed on the vehicle, the infrastructure diameter can be 2.8 times smaller.
This Thesis develops a 0D simulator to evaluate the performance of the proposed hyperloop solution. Solving the aerodynamics of the hyperloop requires solving internal and external Fanno flows. For the latter, the flow combines Couette and Poiseuille effects in an annular domain. Thus, a simplified model for Fanno flows is developed to accelerate the basic modelling. This mathematical approach includes the information of the wall speed and the shape of the domain, avoiding integrating an ODE system. The solution has a deviation in the pressure ratio of 5 % and 10 % in the critical length regarding CFD.
The simulator models all the vehicle thermodynamics, including the compressor, duct, turbine, nozzle, and external flow. This modelling is similar to a Bryton cycle, without a combustion chamber. Also, a model to predict the mass and length of the capsule and its components is included. Thus, the friction losses and the energy and power requirements can be extracted. These outputs are compared with CFD results, with a maximum deviation of 20 %.
Moreover, an optimisation process is conducted with the code to find the most efficient solution for 50- and 150-passenger vehicles. It is found that shallowing less mass flow with the compressor is better, as the energy required to compress the internal flow is higher than the losses on the external channel. Comparing the specific energy consumption of this solution with other means of transportation, the hyperloop is close to the maglev performance. It is also between three and five times more efficient than aeroplanes. Furthermore, the hyperloop is more competitive than the plane in terms of average speed on a route, up to 800 km.
The last part of this work develops a similar model for a middle-scale system. This prototype, which aims to reach 500 km/h, is being designed by Zeleros before the real-scale one. Its simulator also includes the transient effects and the tube thermodynamics, assuming an infinite sound speed. Thanks to this code, the performance in a mission is obtained. The prototype initially increases the upstream tube pressure and reduces the downstream one due to the piston effect, generating an induced speed. At the end of the mission, the flow can be transferred again, and the pressures equilibrate again. This model also predicts the electric motor torque and power and the battery parameters (voltage, current, and deep of discharge).
