Direct Duty Cycle Control For MPPT Digital ImplementationAn algorithm called Maximum Power Point Tracking (MPPT) helps extract the maximum available power from PV module depending on environmental conditions.

Aug 25, 2014Arpita Agarwal, Senior Application Engineer, Ankur Kala, Senior Application Engineer, and Mohammad Kamil, Lead Application Engineer, Freescale | Power Electronics

Maximum Power Point Tracking (MPPT) extracts the maximum available power from photovoltaic (PV) module depending on solar radiation, ambient temperature and solar cell temperature. MPPT based solar charge controller implements an algorithm that maximizes the amount of PV module current applied to the battery.

What is in this article?:

Direct Duty Cycle Control For MPPT Digital Implementation

Solar photovoltaic (SPV) systems are employed in applications ranging from

simple battery charging to complex grid-connected solar inverters. Maximum

Power Point Tracking (MPPT) is an algorithm used in solar applications for

extracting the maximum available power from PV module depending on

environmental conditions. Maximum power varies with solar radiation, ambient

temperature and solar cell temperature. The voltage at which PV module can

produce maximum power is called 'maximum power point' (or peak power

voltage). A solar charge controller embedded with the MPPT algorithm

maximizes the amount of current going into the battery from the PV module. A

low cost 8-bit microcontroller (MCU) can be used to implement a digital MPPT

charge controller. Fig. 1 shows a block diagram of an SPV battery charging

with MPPT.

Fig. 1 Battery charging system utilizing maximum power point control

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The most common topology used to implement MPPT algorithm is Perturb &

Observe (P&O). In this method the system perturbs in a certain direction,

measures voltage and current, calculates Power and compares it with the last

measured value. If the Power increases, the system continues to perturb in the

same direction or else it perturbs in the reverse direction. The amount of

perturb or disturbance introduced can be controlled by implementing a closed

loop control. It is also referred to as the hill climbing method, because it

depends on the rise and fall of the curve of Power against voltage across the

MPP. This is the simplest MPPT algorithm to implement. Fig. 2 shows an SPV

characteristic curve. The MPP voltage at any instant can be higher or lower

from that given (by the SPV manufacturer). Therefore, control output that

decides the operating point should be a signed number so that it can move

forward or backward from the operating point.

Fig. 2 Solar photovoltaic system characteristics showing the maximum power point

Challenges Of Implementing MPPT 

The challenges with the MPPT charge controller are to operate the converter

steadily, regardless of SPV conditions, load changes, and noise in system. A

buck or boost converter is used to implement digital MPPT charge controller.

SPV voltage and current as well as battery voltage and current are monitored

using an analog-to-digital converter (ADC) to implement the MPPT and to

follow the battery’s charging profile. The sense feedback signals are then

processed by an MCU core to calculate next PWM switching tON time. The PWM

module generates the required PWM pattern for a given converter.  ADC

resolution, PWM resolution and core data calculation resolution play an

important role in its steadiness of operation. 

Operating an 8-bit MCU at 8 MHz reduces MCU power consumption, however,

limiting the PWM input clock to a maximum of 8 MHz. Therefore, for 30 kHz

operation the maximum digital number of PWM would be ~266, or 9 bits.  A

general ADC may support 8-bit, 10-bit, or 12-bit resolution. With 9-bit PWM

resolution, maximum 10-bit ADC resolution can be selected, as higher

resolution may not be any advantage.  Choosing a high resolution ADC will

increase conversion time. The control loop output should be a signed number

so the control loop calculation should be in a signed mode. To keep the number

resolution intact, it should be in an 8-bit fraction mode. The 8-bit fraction mode

calculation allows maximum control loop output to be a digital number swing of

-128 to +127. The modulus of maximum control loop output represents the

maximum duty cycle, so it should be either equal to or more than PWM period

value to get maximum resolution for the number of calculations in the control

loop. A Proportional-Integration (PI) control loop compensation block would

also have its own math resolution, and for any given hardware and control loop

performance, it is very tough to find a PI coefficient that can produce zero or

one error at the input of compensation block. Because of all of the above

mentioned limitations, the minimum duty step variation can go up to 2-3% duty

cycle, thus the output would always be unstable across a given reference point

with conventional digital PI swing controller implementation. 

Direct Drive 

Fig. 3 Direct duty cycle control of the switching MOSFET controls the charging current

Direct duty cycle control is the simplest and most effective way to implement

the MPPT algorithm in an 8-bit MCU where even 1-2 bits LSB error in math

calculation can impact the system. Direct duty cycle control controls the duty

cycle from the error produced by reference and actual value sensed by the

controller. The output battery charging current is sensed by the ADC and is

compared with reference current generated by maximum power point

algorithm. Photovoltaic voltage and current are sensed to implement the MPPT

algorithm, so the output of the MPPT algorithm represents a current reference

for control of the charging current. The error (reference - measured)

determines the duty cycle of the switching MOSFET to control the charging

current, as shown in Fig. 3. Based on the error sign, the duty cycle either

increases or decreases. As duty cycle directly controls the system, no

multiplications or divisions are required, and the duty cycle can be controlled

in the order of single LSB, without any error. This allows control of PWM duty

cycle with maximum possible resolution, which produces stable operation even

with dynamic load. Consider a scenario where the inverter is running from

battery and drawing highly non-linear current. In this case, rapid changes in

the charging current are observed and thus MPP keeps on oscillating.

With this MPPT mechanism, you can obtain stable operation around MPP,

resulting in higher efficiency of MPPT in the system.  Thus, this algorithm

enables a tight control over rapidly changing system conditions.