New Control Techniques Electric and Hybrid Vehicle Drive System with

Induction Motor Drives

Szymański Zygmunt

Silesian Institute of Technology Gliwice 44-100 Gliwice, str. Akademicka 2, Poland,

phone: ++49322371688, fax ++49322371537, email: zszymanski@polsl.pl

Abstract. The paper present’s a survey of the wheel vehi-cles drives with electric and hybrid drive system. For electric and hybrid vehicle applications, wheels motor and magnetic circuits cutting motor drives, represented a new attractive solu-tion for their lightness and compactness. The wheels are di-rectly driven by the electric motor, and the gears are not neces-sary anymore. An alternating solution of two induction motor drive system is application of twin rotor induction motor TRIM in a hybrid wheel vehicles. In the modern drive system can be also applied new solution of the traction motor – induction or synchronous motor with cutting stator and cutting rotor mag-netic circuits. The mathematical model of the TRIM traction motor supplied with IPM inverter with different control tech-niques are presented in the paper. Induction motor drive system applied in modern hybrid vehicles, insensitive to parameter and operating condition change, can be achieved using modern control techniques. In electric and hybrid vehicle are applied: Fuzzy Logic Mode Control (FLMC), Sliding Mode Control (SLMC), and Direct Power and Torque Control for Space Vec-tor modulated inverter (DPTC SVM). In the special solution of the hybrid vehicle are also applied a Random Switching Fre-quency Modulation. Control algorithm affirmed high dynamic parameter of the wheel vehicle and limitation of energy con-sumption are presented in the paper. In drive systems with minimization of high harmonic in supply current and voltage of the power supply, has been applied a random modulation mode system with switching frequency. Theoretical analysis of spe-cial construction drive systems with a random modulation technique is described in the paper. The new method control of induction motor in hybrid vehicles are also compared with random switching frequency modulation and with fixed switch-ing frequency modulation. Some variants of the adaptive con-trol system: speed and current adaptive control system and also sliding adaptive control system are applied in the wheel hybrid vehicles. Adaptive controller and controller realized of random modulation techniques are based on DSP controller. The highly dynamic motor control system should assured: energy-saving

work system, optimal control of the petrol and electric motors, and realization of the local and global diagnostics procedures and monitoring procedures of the wheel hybrid vehicles. Some results of the computer simulations performed for mathematical model of the hybrid drive system for specifically work states are presented in the paper. Voltage, current and acoustic noise spectra are used for comparison and it’s concluded that two of techniques are especially useful at lower fundamental frequen-cies. The proposed in the paper control method can substitute classic random modulation techniques with variable switching frequencies in application in electric and hybrid drive system. Some results of numerical calculation of the traction motor drive system were verified of the laboratory experiments per-formed for laboratory model of the hybrid wheel vehicles. New energy-saving inverter fed motor for electric vehicle drive systems makes possible energy sparing traction drive system design. Microprocessor-based hierarchical control systems ensure automatic drive motor control, contact less power supply system operation and implementation of complex control algo-rithms (minimizing voltage and current higher harmonics), power dissipation, and ensuring suboptimum control for normal and emergency operation and drive system diagnostics Key words Twin rotor induction motor, electric vehicle, hybrid vehicle, new control method, random modulation, fixed switching fre-quency modulation. 1. Introduction Clean air legislation is impelling advancements and promises for improvement in electric or hybrid machines performance, drive systems and control [5], [7]. Specially designed electric machines (induction or permanent mag-net motor) have been usually employed in electric vehi-

cles (EVs) or hybrid vehicles (HVs) applications, aiming optimization of efficiency, weight, volume and wider range control [4], [5], [6], [7]. Wheel motor can be used in city cars, electric and hybrid mini vehicles and in spe-cials vehicles. Electric and hybrid vehicles have attracted great interests as a powerful solution against environ-mental and energy problems. With improvement of motor and batteries, some pure electric vehicle with only secon-dary batteries has already achieved enough performance. Modern drive system of road traction vehicles should ensure: environmental safety, high reliability and eco-nomical speed control in specific duty circumstances. A significant improvement in economical and power in-dexes can be achieved by: application of new design drive motors (energy-sparing induction motor, permanent magnet motor, or hybrid drive system which contained petrol and electric motor), application of modern voltage converters controlled by microprocessor systems and optimum control of machines and electric vehicles. Wheels vehicle are usually fitted with petrol motor. However, due to the progress in power and information electronics, the robust induction motor drive and perma-nent magnet motor drives has become an attractive solu-tion for this application since there are no need for com-mutator, switching devices, contactors and others parts subject to wear as necessary in DC series motor and petrol motor. Contact less changing of the direction is simply performed by electronic reverse of the phase-sequence. The highly dynamic motor control system based on field orientation guaranteed optimal driving comfort through smooth traction effort and electrical braking down to standstill. The paper present a survey on electric vehicle control system consisting of energy-saving induction motor, fed by transistor voltage converter based on Intelligent Power Module (IPM) and controlled by single chip microcon-troller. The paper present also a survey on hybrid vehicle consisting of petrol motor and twin rotor, energy-saving, induction motors (TRIM), fed by transistor voltage con-verter based on IPM. The implementation of field ori-ented control, adaptive and sliding mode control are analyzed in this paper. The paper present’s a survey of the wheel vehicles drives with hybrid drive system. For electric and hybrid vehicle applications, wheels motor and magnetic circuits cutting motor drives, represented a new attractive solution for their lightness and compact-ness. The wheels are directly driven by the electric mo-tor, and the gears are not necessary anymore. An alternat-ing solution of two induction motor drive system is ap-plication of twin rotor induction motor TRIM in a hybrid wheel vehicles. An original machine TRIM has a single stator and two rotors. Each core being disc geometry, with stator sandwiched between two rotors. The rotors carry squirrel cage windings, and are mounted on indi-vidual, independent shaft, driving two wheels of an elec-tric part of vehicles. The torque generated by each motor depends on the slip of each rotor and the dimensions of the cores. In the modern drive system can be also applied new solution of the traction motor – induction or syn-chronous motor with cutting stator and cutting rotor mag-netic circuits. The mathematical model of the TRIM traction motor, supplied with IPM inverter, with different control tech-

niques, are presented in the paper. Induction motor drive system applied in modern hybrid vehicles, insensitive to parameter and operating condition change, can be achieved using modern control techniques. In electric and hybrid vehicle are applied: Fuzzy Logic Mode Control (FLMC), Sliding Mode Control (SLMC, and Direct Power and Torque Control for Space Vector modulated inverter (DPTC SVM). In the special solution of the hybrid vehicle are also applied a Random Switching Frequency Modulation. Sliding mode control is capable of providing fast dynamic response drive system, insensi-tive to parameter variation and external disturbances. However, with heritage of past control experiences, the chattering effects about the sliding surface remains a major concern. Results of the control method are limited their practical applications in high performance drive systems. Conventional fuzzy logic controller has been applied in many electric vehicles drive systems, to deal with the non-linearity in control systems. In the paper present’s a control algorithm of the vehicle, which taking into consideration advantages of fuzzy logic and slide mode control method’s. Combined fuzzy – logic, sliding mode control algorithm are presented in the paper. In some types of the electric vehicles profitable solution is application of direct power and direct torque mode con-trol. Control algorithm affirmed high dynamic parameter of the wheel vehicle and limitation of energy consumption are presented in the paper. In drive systems with minimi-zation of high harmonic in supply current and voltage of the power supply, has been applied a random modulation mode system with switching frequency. Theoretical analysis of special construction drive systems with random modulation technique is described in the paper. The new method control of induction motor in hybrid vehicles are also compared with random switching frequency modulation and with fixed switching fre-quency modulation. Some variants of the adaptive con-trol system: speed and current adaptive control system and also sliding adaptive control system are applied in the wheel hybrid vehicles. Adaptive controller and con-troller realized of random modulation techniques are based on DSP controller. The highly dynamic motor control system should assured: energy-saving work sys-tem, optimal control of the petrol and electric motors, and realization of the local and global diagnostics procedures and monitoring procedures of the wheel hybrid vehicles. Some results of the computer simulations performed for mathematical model of the hybrid drive system for spe-cifically work states are presented in the paper. Voltage, current and acoustic noise spectra are used for compari-son and it’s concluded that two of techniques are espe-cially useful at lower fundamental frequencies. The pro-posed in the paper control method can substitute classic random modulation techniques with variable switching frequencies in application in electric and hybrid drive system. Some results of numerical calculation of the traction motor drive system were verified of the labora-tory experiments performed for laboratory model of the hybrid wheel vehicles. Drive system of the hybrid wheel vehicle are presented in fig.1.

Fig.1 Drive system of the wheel vehicle 2. Modern wheel vehicle traction motor For electric vehicle applications, wheels motor drives represented a new attractive possible solution for their lightness and compactness. The wheels are directly driven by the electric motor and the gears are not neces-sary anymore. Because axial flux motors can find their advantageous applications in the low speed, high torque electrical drives. For axial flux motor applied in electric vehicle must be realized: high power/weight and torque/weight ratio, high efficiency and suitable shape to match the constrain space. In the axial flux motors fam-ily, the axial flux PM (permanent magnet) and axial flux induction motor are potential solution [4], [6], and [71]. In the paper described axial flux induction motor Trim and permanent magnet motor [6], [7]. Axial flux induc-tion Trim motor has one stator core with two polyphase windings and two rotors with two different shafts which may rotate independently. All the three magnetic cores (the stator and the two rotors) are in the form of discs with slots for the stator windings and the rotor cages. The machine can be classified as a twin rotor axial flux motor [8]. In this case, the motor can not be mounted inside the wheels but between them. The two rotors with independ-ent shafts make the motor able to output different speeds for the two wheels. That results whenever the vehicle enters in a curve. In this situation the two rotors have different slips that mean that they link different fluxes: the flux distribution tends to keep the motor torque bal-anced. Thus the motor can provide equal torque to the two driving wheels performing as the engine and the mechanical differential of conventional vehicles. There-fore only one inverter is needed to obtain the differential effect. Two identical polyphase windings are connected in series in such a way, that the stator current flows in the same direction in any back to back stator slot. There is one main flux which links the stator windings and the two rotor cages. No flux goes through the stator yoke except the leakage flux. The motor has a small stator yoke which reduces the iron core cost and the iron losses, but long ends windings which results in copper losses. This motor can be designed as single-phase or as three-phase. Induction traction motor with twin rotor axial flux is a physical combination of two motors into one in such

a way, that their magnetic circuits are no longer inde-pendent.

Fig.2 Twin rotor induction motor

Trim motor has special torque characteristics, depending on the degree of interaction between the magnetic circuits of each side of the rotor [5], [6]. The major component of the Trim motor is represented in fig.2a and 2b, with winding omitted. The rotor is on different shafts and may rotate independently. All three magnetic cores are in the form of discs, with slots for the windings cut across the face. In fig.2a and 2b shows details of the cores. The holes for the slots are punched out of a continuous strip which is wound onto a circular former to build up the cores. The space between the slots is adjusted continu-ously during the process. Two identical polyphase wind-ings are mounted on the stator and connected in series in such a way those stator current flows in the same direc-tion down any two back-to-back slots. The rotor carry cast squirrel cage windings. In the simple terms, the ma-chine operates as follows. When the vehicle is steered straight ahead, both driving wheels run at the same speed, and therefore at the same slip. Conditions in the machine are symmetrical and both rotors produce equal armature reaction. Thus all flux, except leakage, linking the stator windings, also links each rotor winding. No flux passes around the yoke of the stator. Both rotors produce the same torque. When the vehicles enter a curve, the inner wheel reduced speed and increases slip whereas the outer wheel increases speed and reduced slip. Therefore the armature reaction from the slower rotor exceeds that from the faster rotor. The same total flux linkage is maintained at the stator winding and the net is that the flux linking the low speed rotor is reduced while that linking the high speed rotor is increased. The redistribution of the flux tends to keep the rotor torques balanced. The difference in the fluxes passes around the stator yoke. As the radius of the curve followed by the vehicle is reduced, this process continues and flux in the stator yoke builds up to the point of saturation. Up to this point, the machine behaves like two machines in series. After this point, saturation limits the flux which can pass around the stator core, and therefore limits the amount by which the rotor

flux linkages can differ. These rotor fluxes are then more or less fixed, and the machine starts to take on the charac-teristics of two machines in parallel connection. The same total flux linkage is maintained at the stator wind-ing and the net is that the flux linking the low speed rotor is reduced while that linking the high speed rotor is in-creased. The redistribution of the flux tends to keep the rotor torques balanced. The difference in the fluxes passes around the stator yoke. As the radius of the curve followed by the vehicle is reduced, this process continues and flux in the stator yoke builds up to the point of satu-ration. Up to this point, the machine behaves like two machines in series. After this point, saturation limits the flux which can pass around the stator core, and therefore limits the amount by which the rotor flux linkages can differ. These rotor fluxes are then more or less fixed, and the machine starts to take on the characteristics of two machines in parallel connection. This machine is de-signed to make use of the magnetic saturation of electric steels. Additionally, as results of the disc geometry, satu-ration will naturally occur in areas of the machine other than the stator yoke. The rotor yokes may saturate, espe-cially at the outer radius, and the teeth of the rotor and stator will saturate, especially at the inner radius. A poly-phase windings sets up a main MMF wave which rotates at the synchronous speed and brings into being a main flux wave which also rotates at the synchronous speed. If a machine is going into saturation in a particular region, the wave will be distorted and will tend to be flat topped in that region, so that the resultant flux waveform will contain space harmonics which must rotate at the syn-chronous speed. If the windings are no ideal, these har-monics fluxes produce harmonics voltages and currents. Supply voltage of the transistor voltage inverter also contains a full spectrum of high harmonics in voltages and in currents. Most of wheel motor has been con-structed as axial flux based, but there are some of the motors have also radial flux construction. Theses motors have been high field intensity across stator windings construction due to a better magnetic path and utilization of standard rectangular magnets, which are easier to handle.

Fig.3 Stator core of synchronous traction motor with cutting

core

The outer rotor may be designed to have permanent mag-net NdFeB Vacodym magnets with high remanence (1,1 T) and coercity (1275 kA/m.) on the inside surface and concentrated windings on the stator. In the motor applied in electric vehicle drive systems must be concerned prob-lems: rise temperature to avoid demagnetization effects, exposition to road shocks, spills, dust and particles, and force demands on the wheel and tire, but mechanical construction of the motor is out of the scope this paper. High number of poles reduced the torque ripple and yields a smaller magnetic yoke, decreasing volume and weight. Also, the permanent magnet area physically lim-its the maximum number of poles. In electric and hybrid vehicles are also applied modern synchronous traction motor with cutting of stator and rotor magnetic circuits.[8]. Scheme of the stator cutting motor are presented in fig3. Magnetic core stator and rotor of that motor is divided for particularly parts. We obtained a traction motor with great torque overloads and good speed control property.

Fig.4 Drive system with weakening field control

Inverter driven induction motors with field weakening operation have been developed for satisfying the re-quirements for large constant power range, run capability in high speed and a fast response to the load variation. Rapid development of power electronic devices with low cost and high reliability, such application is getting widen to AC electric vehicle. Particularly, it has been proven that induction motor applied in those applications, thanks to the peak torque capability, ruggedness, high reliability, small size and economical cost. The capability curve of the inverter driven induction motor is show for fig. 4. Constant torque region is U/f region where air-gap flux fixed, constant power region are field weakening region I and II. In field-weakening region I, voltage and current are restricted within maximum values: Ulim, Ilim,. Since the slip increases from rated slip to maximum torque slip as the speed increases, the slip frequency increases like nearly strait line. As the slip frequency increases with the injection current fixed, inductance values must decreases as the speed increases. As both voltage and slip fre-quency are fixed and current decreases, the inductance parameter value should increases in field-weakening region II. For solution this problem can be applied a modern method based on application of FEM to calcu-lates equivalent circuit parameters of induction motor in weakening –fields region. [3], [4].

3. Mathematical model wheel vehicle drive

system The paper present three control method of induction motor drive system: field oriented method), adaptive control method and sliding mode control method: [3], [6], and [7]. In adaptive control method of induction drive system is performed a mathematical analysis of wheel vehicle drive system droved trim induction motor and two single induction motors. System of differential equations described a dynamic state of the induction motor with one rotor are presented by (1):

( )

( )

( )( ) ( )

( )

( ) ( )

( ) ( )

d

dtd

dt

d

dt s

d

dt s

ddt J

pJ

p

s

s r s

s

s

s

s r ss

s

s

r

s

s r

s

r

s

s

r

s

s r

s

r

s

s

r

ss r

s

s r

s

M

eM

S

K u

K u

K u

K up KL T

T L

α

α α α

β

β β β

α

α α β α

β

β β α β

β α α β

ψψ ψ

ψψ ψ

ψψ ψ ψ

ψψ ψ ψ

ψ ψ ψ ψ

α α

α α

β β

β β

σ

= − + +

= − + +

= − − +

= − + +

= −⎡⎣⎢

⎤⎦⎥−

=

Ω

Ω

Ω 32

3

2

2

( )( ) ( )

L L LR Ms r

s

s r

s

−−⎡

⎣⎢⎤⎦⎥2 β α α β

ψ ψ ψ ψ

(1)

where:

SM

SR

M

R

M

S R

S

S

R

RK L

L K LL

LLL

RL

RL= = = − = =, , , , ,σ α

σβσ

12

System of differential equations described a dynamic state of the induction motor with one rotor are presented by (2):

[ ]

[ ]

222

2212

111

111

22,2

2

11,1

1

12,1,2

22

22222

22,1,1

11

11111

22,

11,

MM

MoM

MM

MobM

rrsM

TsM

rrsM

TsM

rrr

ssr

rr

rrrsrr

rrr

ssr

rr

rrrsrr

rrs

rrs

ss

sssss

Ddt

dJMM

Ddt

dJMM

iMiM

iMiM

dtdiM

dtdi

Mdt

diLdt

diLiRu

dtdi

Mdtdi

Mdt

diL

dtdi

LiRu

dtdiM

dtdiM

dtdi

Ldtdi

LiRu

ωω

ωω

φ

φ

σ

σ

σ

+=−

+=−

⋅∂∂

=

⋅∂∂

=

++++=

++++=

++++=

(2)

(State observer defined for fixed coordinate αβ in in-

duction motor vector control without rotational speed sensor, for magnetic flux connected with rotor winding

may be presented in the form of equation (3):

[ ]iiIuILJITIT

LJITTT

LITTrs

sS

RR

M

RRS

M

RSK

xxdtd

−⎥⎥⎦

⎤

⎢⎢⎣

⎡+

−⎥⎥⎥

⎦

⎤

⎢⎢⎢

⎣

⎡+

⎥⎥⎥⎥⎥

⎦

⎤

⎢⎢⎢⎢⎢

⎣

⎡

+−

⎟⎟⎠

⎞⎜⎜⎝

⎛−⎟

⎟⎠

⎞⎜⎜⎝

⎛ −+−

= −−

−−−

−−−

− 00

1

1

111^

^

^

^

σω

ωσσ

σσ

(3) where:

x s s s s

T

i i−=⎡⎣⎢

⎤⎦⎥

^ ^ ^ ^ ^,α β α βψ ψ

, [ ]s

Tu u us s−= α β ;

I−=⎡

⎣⎢

⎤

⎦⎥

1 00 1

; J−=

−⎡

⎣⎢

⎤

⎦⎥

0 11 0

where estimative angle ρ^ of the magnetic field vector location, connected with rotor windings for transforma-tion system of variables αβ is equal: ρ=arctgΨrα/ Ψrβ. On the ground of analysis global stability of drive system with state observer applied of the research Lapunow function method calculate a variability section of correction feedback K≤0. [3], [6], [7]. Adaptive algo-rithm of motor speed ω^ with adaptive period Ta can be done in discrete forms by equation system (4):

n n i a n

n n P n

K TK

+

+ +

= +

= +

1

1 1

ω ω εω ω ε

* *

^ *

(4) where Ki and KP >0. Adaptive error can be calculated with relation (5):

^^^^

ψψ βαααββε

rssrss iiii ⎟⎠⎞

⎜⎝⎛ −−⎟

⎠⎞

⎜⎝⎛ −= (5)

In the sliding mode controller of electric vehicle all prob-lems in the low speed region are caused by use of inac-tive or zero vectors of the inverter. Therefore a possible solution would be to avoid using these zero vectors, but this leads to a high inverter switching frequency. How-ever, if the inactive voltage vectors are only removed in transient conditions, it is possible to achieve torque and flux control, even in the low speed region while lowering the switching frequency in steady-state. For the transient conditions the switching scheme is based on sliding mode control. The equivalent control is defined as the input which zeroes derivatives of sliding mode. For stator flux and torque control are selected as (6):

TTSS obcesws

x y −=−−−= ΨΨ/, (6)

To find the equivalent control Vseq the derivatives of (6) are taken:

TTSS obceyswsx

^^^

/,^ −Ψ−Ψ ==−

(7)

Supposing that the set values for torque and stator flux are constant, these equations are simplified:

TSS eysx^

/

^^

^

=Ψ=− (8)

With the machine equation rewritten in a reference frame fixed to stator flux these equation become:

( )

⎟⎟⎠

⎞⎜⎜⎝

⎛Ψ+Ψ=

=+=Ψ

IINS

SxfV

syzssyzspy

xzszs

^

,,/

^1,,

^

23

^

(9)

with f1(x) and f2(x) nonlinear function of the motor state x. [3], [6].

4. Modern drive control system Sliding mode control is capable of providing fast dy-namic response drive system insensitive to parameter variation and external disturbance. However with the heritage of part control experience, the chattering effects about of sliding surface remains a major concerns and as a results it has limited it’s practical applications in high performance drive system. Many researchers investigated the possibility of merging the algorithm of Fuzzy Logic in their sliding mode control design to overcome its high control gain effect and alleviate the chattering effect and improvement the dynamics of the drive. Conventional Fuzzy Logic controller by its own has been applied to many engineering problems to deal with the non- linear-ity in the control systems. It has been used to overcome to need for a precise modeling of the controlled system but only the systems behavior has to be known and this knowledge can be acquired with some experimental graphs. The paper present a comparison of the three con-troller performances in induction motor drive. The com-parison criteria were based on the implementation com-plexity and dynamics response of the drive system. The effectiveness of such controller was tested via simulation, when they were applied to the outer-loop speed regulator of an indirect vector drive. The conventional Fuzzy Logic controller has achieved a considerable improvement of the drive dynamics in contrast to those obtained with Fuzzy Logic Mode Control an d conventional Sliding Mode Control. In Basic Sliding Mode Control, a second order nonlinear system can be modified in stateλ–space plane by state equations

( ) ( )utxatxax

xx,,2

1 2

+=

=∗

∗

(10)

where: dim x= n and dim u = m, n>m. From (10) ensured that: [x] is the state vector of the sys-tem, a(x,t), b(x,t) represented vector fields in nonlinear function, u is the control input to the system. VSC im-plies the design of switching surface s(x) =0 of an appro-priate m dimensional, which is a lower order than the given plant to represent the desired sliding mode dynam-ics. The switching surface can be defined by: s(x) = C x where: s(x) = [s1(x), s2(x), ………..sn(x)]T and

[ ]cccC Tn

TT T

121 .......,,= T (11)

thus: si(x) = ciT x =0

The variable control structure is described as: u = u+ (x), where s(x) > 0, and u = u- (x), where s(x) < 0 It follows from the above formulation that system trajec-tory is forced to reach the switching surface in a finite time with a small overshoot. Once the system on the switching surface it slides towards the origin, making the system to be in the sliding mode, following the desired dynamics. The control signal is than designed to satisfy the existence of the sliding mode by satisfying the the reaching condition given by:

( ) ( )xsxs∗

= < 0

This is known as the direct switching function. The ob-jective of this approach is to design a controller so that system follows a prescribed dynamics and becomes in-sensitive to parameter variation. Furthermore, a fast dy-namic response without overshoot is highly desirable. This can be achieved by a good selection surface defined by:

S(x) = C x1 +x2 , C > 0 The control signal based on this approach is of the form:

US = ϕ1 x1 + ϕ2 x2 where::

⎪⎭

⎪⎬⎫

⎪⎩

⎪⎨⎧

≤

≥=

⎪⎭

⎪⎬⎫

⎪⎩

⎪⎨⎧

≤

≥=

0

0

0

0

2

2

2

2

2

1

sxsxsxsx

if

if

if

if

ξ

χ

β

α

ϕ

ϕ (12)

Each gain constant must be selected to satisfy the reach-ing condition given in (12), which makes the VSC system globally asymptotically stable. In Basics of fuzzy control, a Fuzzy logic contains linguis-tic control rules that are developed based on human ex-periences and intuitions. In most engineering control applications, the fuzzy logic rules are simply expressed as collection of: IF …THAN, rules, composed with fuzzy sets A, B for controller inputs: x and y respectively, and C is the fuzzy sets for output z, IF x is A and y is B than z is C The fuzzy sets are usually expressed in linguistic labels as: NL, NS, ZO, PS, PL respectively. The relation ship between the control inputs (x, y) and output z is devel-oped using the fuzzy set theory, and can be described as fuzzy relation matrix using assigned membership func-tion. Having fuzzy relation matrix and a membership grade of the condition part for each rules, the degree of membership for the controller output characterized by linguistic labels can be obtained by adopting the max prod inference rule. The membership grade for each linguistic label designated by ϕ is computed for all rules: µ U, X (ϕ) = max [prod (µ R (x, ϕ), µ (xi))] From (13) the firestrength of each output fuzzy set is determined, which indicates how much they contribute to the inferred result for given inputs x and y. The inferred fuzzy control action is than defuzzified to obtain the control output numerical or crisp value, where Y is the inferred control action and Y2 is the defuzzyfied numeri-cal output. There are many methods of defuzzyfication but the Centre of Area method (COA) is widely used in

the defuzzyfication process. It can be computed be defin-ing the contour of the inferred fuzzy control action and then applying the following equation

∑

∑

=

== N

kk

N

kkk

a

xaY

1

10 (13)

where, N is the range of elements in the universe of dis-course, xk is k element in the universe and ak is the cor-responding degree of membership In Combined Fuzzy Logic Sliding Mode Control we can appllied next procedure. In most designs VSC -SLM systems, the transient dynamics of the reaching mode are not defined. Thus, the speed with which the sliding sur-face is reached and the amount of control chattering around it is not specified. Therefore, an alternative design of VSC –SLM is required to give the desired transient dynamics in the reaching mode as well as in the sliding mode. This law is often called a reaching law, in which the dynamics of the sliding surface s(x) are specified. These dynamics are described by a differential equation of the form

( ) ( )sKsignxs −=∗

, K>0

It follows from the above equation that the speed with which the system state approach the sliding surface can be predetermined, where the rate of convergence is given by K. Thus, the control signal of the reaching law can be defined by computing the time of derivative of s(x) along the reaching mode trajectory of system (10) which yields

( ) ( ) ( ) ( )sKsigndxdstxub

dxdstxaxs −= =+

∗

,, (14)

Rearranging equation (14) for reaching control law, gives

( ) ( ) ( ) ⎥⎦⎤

⎢⎣⎡ += ⎥⎦

⎤⎢⎣⎡

−

sKsigntxadxdstxbu dx

dsR ,,

1

(15)

This law forces the system trajectory to reach the sliding surface s(x) at a constant rate defined by the value of control gain K. Selecting a large value of K shortens the reaching time but it would be on the expanse of causing sever chattering once the system states hit the sliding surface. In contrast, if a smaller value of control gain K is selected, it results in less chattering while on the sliding surface. The reaching time in this case, however, would be long and as a result the system is still susceptible to parameters variation and external disturbance. Fuzzy logic concept can be usefully integrated with the current control design in the reaching mode to regulate the value of control gain K, which is solely responsible to control the reaching time. The value of K has to be selected ac-cording to some rules which are based on the position of the system trajectory with respect to the sliding surface on the phase plane Direct Power Control (DPC) for PWM converter is based on instantaneous control of active p and reactive q power flow to active load [3, 4]. In classical approach of DPC

there are two power control loop with hysteresis com-parators and switching table. Therefore, the key point of the DPC implementation is sufficiently precise and fast estimation of the instantaneous line powers.

Fig.5 Block control scheme of wheel vehicle drive with DPTC control system The most significant drawbacks of the hysteresis-based DPC are variable switching and high sampling frequency. Introducing a Space Vector Modulation (SVM)in control strategy allows to eliminate the both mentioned prob-lems. Moreover, the line voltage sensors can be replaced by virtual flux estimator, which introduces technical advantages to the system. Such control system replaced hysteresis comparator and switching table [4, 5]. Simi-larly like DPC, for classical Direct Torque Control (DTC), the command stator flux Ysc and commanded torque Msc values are compared with actual stator flux Ys and electromagnetic torque Mec values in hysteresis con-trollers. Therefore, the well-known disadvantages of DTC are: variable switching frequency, switching polar-ity DC link voltage, current and torque distortion caused by sector changes as well as high sampling frequency requirement for digital implementation of the hysteresis controllers. All above difficulties can be eliminated when, instead of the switching table, a SVM is used. Hence, DTC-SVM strategy for control of the supply system composed with inverter and induction motor are presented for fig.5 5. Random modulation technique for Trim

induction motor Adjustable speed drives have reached a state, where they have became armature component in much professional application, particularly in the wheel vehicles. The main reasons are their capabilities of energy savings, improved automation performance, and also the cost is steadily decreasing. Sensor less control, power converter design and pulse width modulation PWM is important for the wheel vehicles drive performance in respect to current harmonics, torque ripple, and also acoustic noise, emitted from: induction motor and supply system [1, 2]. Different approaches are used in PWM including switching with lower frequency [1, 2], switching with high frequency (greater than 17 kHz) [1], [2], [6], or using a random switching frequency - RSF [1], [2]. The method RSF is very efficacious, because the average switching fre-

quency can be kept low as can the acoustic annoyance [2], [7]. One approach uses the space vector modulation technique extended with a variable switching frequency operation, which effectively reduces the acoustic annoy-ance, but problems arise in the control system because then a variable sampling frequency in the controller are needed if the modulator and the controller shall operate in synchronism [2]. Another method shifts randomly between lagging and leading edge modulation [1], which effectively gives a random modulation but problems appear in the sampling of the currents without using any anti-aliasing filter. The original new method RSF pre-sented in the paper operating at a fixed switching fre-quency, but the pulses are randomly positioned within the switching period. In that method is randomly changes the duration of zero vectors: 111 and 000 [1], [2]. RSF method is applicable to power converter, which supply-ing of the traction motors in wheel vehicles, without any neutral connection. All random PWM techniques have common property that the switching frequency is con-stant. As stated above this may ease the implementation of digital controllers, which often are synchronized to the switching of the inverter, which in turn is controlled by the PWM unit. Having excluded the switching frequency as the parameter to randomize, it seems that the pulse position is the only quantity which can be randomized, while still keeping the average voltage produced by the inverter fully controllable within each switching interval. The fundamental idea behind random pulse position techniques is that the mean voltage measured across one switching interval is independent of the position of the pulse. This degree-of-freedom may be utilized in various ways: from a theoretical point of view, the only con-straint is that a pulse must not extend beyond the bounda-ries of the switching interval in question. That constraint may be met in a number of different ways, but the litera-ture dealing with random pulse position has focused almost exclusively on one simple variant, namely the so-called lead-lag random pulse position technique originat-ing from [6]. Sketches of the investigated method are show in fig.4 including the method of [6]. The symbols: qa, qb, qc, indicates the PWM switching function for the three phases, and T is the switching period. Method RLL (Random Lead–Lag Modulation- fig.4a): the pulse posi-tion is either commencing at the beginning of the switch-ing interval, or is tailing edge is aligned with the end of the interval. The choice between leading and lagging modulation is controlled by a random number generator. Method RCD (Random Displacement of the Pulse Cen-ter-fig.4b): show a method where the pulses are mutually center-aligned as in space vector modulation SVM, but the common pulse center is displaced by the amount ωcT from the middle of the period. The parameter ωc is varied randomly within a hand limited by the maximum duty cycle. Method RZD (Random Distribution of the Zero Voltage Vector-fig.4c): In three phases, three wire systems the duration of the zero voltage vectors does not alter the phase voltages. This fact is utilized in the random distribution of the zero voltage vector, where the proportion between the time duration for two zero vector states and 000 is randomized in a switching cycles. All pulses are center-aligned as in standard SVM. Method RSF (Random Switching Fre-

quences-fig.4d): in this method the switching period is randomly varied (T1, T2, T3,) within a limited interval. The method RLL, RCD and RZD are all operating with fixed switching frequency. Two different limitations in respect to randomization exist in RCD and RZD. In the RCD the maximum duty cycle of: qa, qb, qc gives the maximum possible displacement of the pulses.

Fig.6 Results of computer simulation in application of FL-SLM

mode control This means that at high modulation indices the available displacement interval will be reduced... In all cases, the modulators produce active vectors of duration identical to the SVM, exactly the same average voltage vector ūr is generated by the inverter irrespective of randomization method. In order to implement the random modulation strategies it is necessary with flexible PWM unit. Fig.4 shows how the two new modulation strategies can be implemented. The reference for the modulator is the average voltage vector defined by is magnitude U and its position q. This is used in standard space vector modula-tion. The output is three duty–ratios (Da, Db, and Dc). Those are used to calculate the maximum possible dis-placement αmax by comparison of their magnitudes. The actual displacement is calculated by randomizing of αmax and depending on whether RCD or RZD is used two compare levels (P1, P2) in timer are calculated and used for qa. Correspondingly are P3-P6 also calculated for the two other phases. If RCD is used, then equal αcT, and if RZD is used, α is equal to the duration of the zero-vector (000) t0. Lead – lag modulation is implemented by using only one compare level P1 for each phase.

Fig.7 Results of noise analysis Random Modulation Technique 6. Computer simulation and test results On the basis of mathematical model of wheel vehicles with electric and hybrid drive system was performed a computer simulation with applied Matlab - Simulink procedures. Results of computer simulation presented in fig.6, 7. The control is implemented in a combined DSP (ADSP-21 062) and microcontroller (SAB C167) system. The DSP handles all calculations in real-time using float-ing–point arithmetic, including the task of generating random number s to the random PWM. A Bruel- Kjaer Pulse Multi Analyzer and Hameg harmonic analyzer system are used as Dynamic Signal Analyzer. Voltage and current are sensed using Tektronix probes and ampli-fiers. Experiment is done for the three random modula-tion techniques with fixed switching frequency. Included are also results for classic random switching frequency technique with the minimum switching frequency fmin=4 kHz, maximum switching frequency fmax= 6 kHz and for fixed frequency operation at 5 kHz. Comparing the volt-age spectra distinct harmonic voltage components appear in the case of fixed switching and random lead-lag, while the power spectra is much more smooth for the other three method. The most smooth power spectra are zero-vector distribution and from a subjective point of view the acoustical noise from induction motor is the least annoying. At higher fundamental frequency more pro-nounced harmonics are presented in all measured spectra except for the random switching frequency technique. When random switching frequency is used the control loops have to be modified. In the RLL strategy a correct current sampling is very difficult to achieve because of the asymmetric modulation. Space vector modulation at low modulation index with fixed switching frequency

assures at low current ripple. Using RS, RZD or RCD will increase the peak to- peak ripple, but not as the poor-performing RLL technique. The acoustic noise is more pleasant or rather less annoying for RCD, RZD and RD both at low and high modulation index. Some results of noise analysis are presented in fig.7. 7. Conclusion New energy-saving inverter fed motor for electric vehicle drive systems make possible energy sparing traction drive system design. Microprocessor-based hierarchical control systems ensure automatic drive motor control, contact less power supply system operation and imple-mentation of complex control algorithms (minimizing voltage and current higher harmonics), power dissipation, and ensuring suboptimum control for normal and emer-gency operation and drive system diagnostics. Universal solution (with some necessary modification) can be ap-plied not only in vehicle drive system. From the power capability and the principal dimensions, the axial flux PM and induction motors can be mounted into the wheels to realize the driving strategy. A new calculation family of random methods for three-phase power converter, operating at fixed switching frequency is proposed. Two different method for randomize the pulse width or pulse position have been shown to have the same performance with respect to acoustic noise abutment as random switching frequency at low fundamental while the ran-dom switching frequency method has the best perform-ance at higher fundamental frequencies. References

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[2] M.M. Beck, F. Blaabjerg, J. K. Pedersen, “Random modula-tion techniques with fixed switching frequency for three-phase power converter”. IEEE Transaction on Power Elec-tronics. Vol. 15, no 4, July 2000r, pp: 753- 760

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