Modeling of Full Electric and Hybrid Electric Vehicles

Modeling of Full Electric and Hybrid are automobiles with more electric components than ordinary vehicles. For HEVs, this means an Internal Combustion Engine coupled to electrical machinery, power electronics, and energy storage (battery, supercapacitors) (ICE). The design of a new vehicle must be interdisciplinary to account for the dynamic interaction of all vehicle components and the power train.

Simulation and Modeling of Full Electric and HEVs:

Because prototyping and testing are expensive and complex activities, vehicle designers need modeling and simulation to discover the best component sizing, energy control strategy, and vehicle consumption. Accurately simulating all components based on their physicochemical properties is difficult. Automotive designers employ a variety of commercial simulation programs.

FEV and HEV modeling:

The vehicle’s powertrain is made up of many interconnected components that exchange energy and information. An ICE and fuel tank are also considered for HEVs and Plug-in Hybrid Electric Vehicles. A multidisciplinary approach analysis is necessary to describe them. To build a vehicle, a thorough system analysis is necessary, which includes controlling the energy from the on-board source, optimizing the electric and electronic devices, and designing the mechanical connections between the various power sources. So, the full simulation model must accurately depict the power flux exchanges between system components to assist designers during the study.

Map Based Modeling:

Each component can be modelled using either an equation-based or a “map-based” method. Each subcomponent is described by its quasi-static characteristic equations, which must be solved to generate the output responses. The biggest disadvantage is the computational load required to solve the model equations.

Using a map-based method, each sub-model is represented numerically by a series of look-up tables. The map must be calculated off-line using a component model equation or experimental data. This method uses less compute but is not parametric and involves “off-line” map manipulation to alter a component parameter.

Object Oriented Causal Method:

An object-oriented causal method can be used to build models. In reality, the model can be divided into subsystems. Each subsystem represents a vehicle component and contains equations or a look-up table describing its behavior. So each item has input and output variables that can be connected to other objects.

So each object is independent of the others and may be validated, edited, or replaced without affecting the rest of the model’s equations. A power flux across subsystems can be defined by connecting an object’s output variable to an input signal of another. Modularity of this technology enables for diverse and sophisticated configurations by just rearranging the object connections.