Regenerative Intelligent Brake Control for Electric Motorcycles

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.

Review of Soft Computing Models in Design and Control of Rotating Electrical Machines

“…Husain [52] 2018 Fuzzy expert system transformers via dissolved gas analysis test S.; Sedraoui Kahla, el al. [53] 2018 Combination of standard onoff strategy with fuzzy logic Maximize the power point tracking of wind energy Aguilar [49] used a simple fuzzy logic algorithm for the intelligent brake control of an electric motorcycles engine in order to recover the maximum energy in braking processes while maintaining the vehicle's stability. The success of the employed method is very bold, such that the results of comparing the regenerative system with the ABS in a low adhesion condition have been presented in Figure 9 in terms of mean deceleration (a) and distance (b).…”

“…(a) (b) Figure 9. results of the study by Aguilar [49] in terms of (a) mean deceleration and (b) distance.…”

“…Such composed system is called fuzzy neural, neural fuzzy, neuro-fuzzy or fuzzy-neuro network, or ANFIS in which Figure 9. Results of the study by Aguilar [49] in terms of (a) mean deceleration and (b) distance.…”

Low-Cost FPGA-Based Electronic Control Unit for Vehicle Control Systems

“…The measurement of the vertical force (F z ) applied to the tire by the external force of the swingarm is calculated by measuring the deformation of the tire. Finally, to model the electrical system, the motor map provided by the manufacturer is used as well as a model of the power inverter (see [30]). As can be seen, the power inverter output is modelled as a second order system, Equation (9), where s is the throttle percentage; normalf(s) = 10.007 s2 + 0.134 s + 1 .…”

“…Therefore, a controller based on fuzzy logic, which is widely known for its robustness and widespread use in control systems in vehicles, was programmed. Since the development of this algorithm was not the main objective of this work, a controller previously developed by our research group [30] was used. The Simulink ® model optimizes the parameters for the specific task.…”