PhD Thesis - Cranfield University

Chapter 5
output fuzzy set is produced. The final output of the controller is single scalar value
representing the control action performed on the input variables.
As fuzzy logic permits systems to be controlled by heuristic representation of how the
system should behaves [114], this feature is employed to generate the battery maximum
power (P battmax) reference output of the EMS. In this application, the rule base is designed
using heuristic reasoning of the energy management strategy. Base on the following
postulates, dictated by the energy balance equation of vehicle kinetic energy to ultracapacitor
potential energy (5-28), a fuzzy inference system (FIS) is implemented.
Heuristic reasoning- 1
“ If the vehicle is travelling fast and close to its maximum velocity, and the ultracapacitor
state of charge is high, then reduce the maximum battery power limit so that the power
management shell will be forced to use the energy stored in the ultracapacitor and
accordingly bias the feed forward reference power trajectories towards the ultracapacitors,
thus reducing its state of charge ”
Heuristic reasoning- 2
“ If the vehicle is at medium velocity, whereby a rapid power demand to accelerate the
vehicle could occur, but the ultracapacitors are at a low state of charge, then increase the
battery power limit so that opportunity charging of the ultracapacitors by the battery system
can take place ”.
The vehicle speed input is defined by three membership functions, {Slow, Medium, Fast}.
Similarly, the ultracapacitor SoC membership function is defined by {Low, Medium, High}.
With x 1 and x 2 as the state variables and y representing the output variable, the FIS is
represented as a two input one output system in a generic form of conjunctive rules as
follows:
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