Abstract
Vehicle models whose propulsion system is based on electric motors are increasing in number within the automobile industry. They will soon become a reliable alternative to vehicles with conventional propulsion systems. The main advantages of this type of vehicles are the non-emission of polluting gases and noise and the effectiveness of electric motors compared to combustion engines. Some of the disadvantages that electric vehicle manufacturers still have to solve are their low autonomy due to inefficient energy storage systems, vehicle cost, which is still too high, and reducing the recharging time. Current regenerative systems in motorcycles are designed with a low fixed maximum regeneration rate in order not to cause the rear wheel to slip when braking with the regenerative brake no matter what the road condition is. These types of systems do not make use of all the available regeneration power, since more importance is placed on safety when braking. An optimized regenerative braking strategy for two-wheeled vehicles is described is this work. This system is designed to recover the maximum energy in braking processes while maintaining the vehicle’s stability. In order to develop the previously described regenerative control, tyre forces, vehicle speed and road adhesion are obtained by means of an estimation algorithm. A based-on-fuzzy-logic algorithm is programmed to carry out an optimized control with this information. This system recuperates maximum braking power without compromising the rear wheel slip and safety. Simulations show that the system optimizes energy regeneration on every surface compared to a constant regeneration strategy.
Highlights
A large number of countries are adopting policies to increase the number of electric vehicles in their fleets
The regenerative brake distance is lower when the vehicle is equipped with the conventional. This is due to the vehicle is equipped conventional is dueSimilarly, to the fact that the rate torque cannot with brake the as efficiently as the conventional a second test regeneration is has been facttothat the regeneration ratesurface is limited to WithInthis maximum rate, the regenerative brake simulated on a low adhesion
A second test is has been simulated on a low adhesion surface simulated on a the low regenerative adhesion surface
Summary
A large number of countries are adopting policies to increase the number of electric vehicles in their fleets. Fuzzy logic [5,6], sliding control [7,8,9], control by artificial neural networks [10,11] and nonlinear control [12,13] are examples of the most used control methods These systems try to optimize the longitudinal and lateral force in the tire, obtaining the maximum available force in the wheel-road contact during braking and traction processes. The system proposed here aims to improve the safety of electric vehicles as well as save energy in a novel way It makes use of a fuzzy control that estimates the road adhesion and determines the optimal regenerative braking torque without causing the wheel to slip.
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