Used Taxi – Motor control combines various control algorithms
The electrification of motor vehicles is advancing rapidly and the efficient control of electric motors is becoming ever more important. Thus the Hybrid vehicles of every kind currently serve as a bridge technology until high-capacity electrical energy storage systems are available at reasonable prices, enabling the production of long-range all-electric vehicles.
Taxi Sales: In common, the Car manufacturers and their suppliers are working hard to develop economical new vehicle models with the aim of reducing both fuel consumption and CO2 emissions. A central element of both approaches is an electric motor which, in the case of the power train, is used either in combination with a conventional internal combustion engine or as an independent source of power.
The algorithms used must be adapted to the respective motor and application so that the electronic controller com mutates the motor optimally at all times. Failure to adapt these correctly may lead to undesired effects such as irregular running and excessive noise, which together have a negative impact on the degree of efficiency that can be achieved.
The Motor control combines various control algorithms depending on the application. They are field-orientated control (FOC) combined with PID regulation systems for controlling rotor speed, torque and flux. the Clarke/Park transformation is used to transform the phase currents measured from a stator-based three-dimensional system to a rotor-based two-dimensional system. These transformed variables, the current rotor position and a target position specified by the application, or a target rotational speed, are taken as starting points for the control algorithms.
As a key component, the rotor position sensor has significant influence on the performance and efficiency of the motor system. The current rotor position can be either directly determined with a sensor or estimated using a complex calculation system. The latter method also known as sensor less angle detection which is based on the logging and evaluation of two actively controlled phases.
Thus the Efficient software algorithms, powerful micro controllers and highly efficient electric motors will make this possible. A higher level of integration leads to leaner and cheaper motor control systems that can be used in applications above and beyond those presented here. Until then, the maximum use must be made of the energy available in the form of fuel and/or electrical power in hybrid vehicles.
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