Brushless motor power and efficiency analysis
By Emrik Joner, last updated: 18-11-2020
Understanding efficiency is the first step to improving the performance of devices and vehicles containing brushless DC (BLDC) motors. This article explains the key formulas for calculating brushless motor efficiency and demonstrates how they can be used in experimental situations.
There are two main efficiencies to consider in a brushless system: motor efficiency and propeller efficiency. In order to focus on motor efficiency, we will simplify propeller efficiency and say that the bigger the propeller, the higher its efficiency. Motors, on the other hand, have a high efficiency when spinning at high speed with relatively low torque. Operating at high torque results in the motor heating up and losing efficiency. That said, the reduced efficiency might be a worthy compromise in order to use a larger, more efficient propeller and to avoid using a gear box, which adds complexity and leads to heat losses.
This article will help you gain an understanding of how a brushless DC motor operates by providing examples with real data. If you are a drone designer, this knowledge will also help you develop strategies to maximize the flight time and payload of your vehicle. In the experiments described, we use an RCbenchmark thrust stand for data acquisition and powertrain control. The theoretical analysis is done in Octave.
There are several key formulas for understanding brushless motor performance:
The torque-speed plot and mechanical power:
Let’s first look at formula 2, which describes how to calculate mechanical power:
Mechanical power is the product of torque and RPM, so when there is either no torque or no rotation, no power is produced. Figure 1 provides a visual reference for what this looks like in practice, where we present data from several motor tests.
Figure 1: Mechanical power for a 1500Kv brushless DC motor
Along the horizontal axis you’ll see several blue circles, these data points were recorded during a no-load motor test. As you can see, when the motor is spinning freely with no load (i.e. no propeller), no torque is generated. An increase in voltage increases the motor’s speed along the horizontal axis, but the mechanical wattage remains at zero. The dynamometer used for the test confirmed the results, also indicating zero torque and zero mechanical power.
The other extreme is to have no rotation speed while slowly increasing the torque, achieved by sending power to the motor but not letting it spin. In theory, this mode of operation would produce a vertical line of data points along the vertical axis with increasing torque but no speed. In practice, motors used by UAVs and drones are not designed to work at very low speeds and would overheat with high torque. We did not want to subject our motors to this much stress, so we only performed this test at low torque, which is why there is only one data point above zero on the vertical axis.
In reality your motor will operate between these two extremes. The six other power curves in figure 1 demonstrate the results of tests performed with unobstructed motors with propellers. Each dataset represents a different propeller, with the corresponding sizes listed in the legend on the right-hand side (diameter, pitch).
The torque-speed plot and electrical power:
Electrical power can be determined experimentally or theoretically, and it can be a fun exercise to compare your test results to your theoretical calculations.
When calculating electrical power we use formula 3 where it is the product of current and voltage. The data points in figure 3 represent the test result from the motor equipped with propellers of different sizes and pitch. Similarly to the 3D display of mechanical power in figure 1, the electrical power is proportional to the motor’s torque. However, even when there is no rotation (RPM = 0) and torque is applied, there is still production of electrical power. This is unlike mechanical power, where for all torque values at 0 RPM no power is produced.
Each curve represents a different load (propeller) with speed and torque values plotted The theoretical values are displayed as a 3D plot represented as a coloured surface, the brighter the shade, the higher the electrical power at that point.
Figure 3: Electrical power for a 1500Kv brushless DC motor
To calculate a motor’s electrical power theoretically we use formula 4. To allow us to input values into the formula, we replace ‘mechanical power’ with the right side of formula 2, and ‘heat losses’ with the right side of formula 5, to give formula 6.
Here, R represents the resistance in the circuit generated by the motor (inversely proportional to the torque). The theoretical model assumes that the Kv does not change, which is not exactly true due to the electronic speed controller (ESC). We also simplify heat losses as a simple resistance, while in a real circuit there is a more complex impedance. These distinctions lead to differences between the theoretical and experimental results.
The efficiency of a motor is determined by dividing the mechanical power by the electrical power (formula 1). A goal for vehicle design is therefore to maximize this ratio and optimize the overall system efficiency by using the biggest propeller possible without overloading the motor. This is why testing is so important. Using a giant propeller would drastically increase the propeller efficiency, but the motor would struggle so much to make it spin that its efficiency would be ridiculously low. Doing the opposite isn’t great either as making a tiny propeller spin very fast would lower both the motor and the propeller efficiency. The best solution is to balance both efficiencies to get the highest overall performance and system efficiency. To achieve the highest efficiency the motor has to operate in the yellow zones of Figure 4 and 5.
Figure 4: Motor efficiency for a 1500Kv brushless DC motor
Figure 5: Motor efficiency for a 1500Kv brushless DC motor in 3D
The three graphs in figure 6 demonstrate how motor parameters vary and how to optimise them to achieve higher performance.
Figure 6: Parameters contributing to motor performance
The trend lines on these graphs can help you understand how to optimise your motor’s performance and operating conditions, whether you’re aiming for maximum flight time for your transport drone or maximum power for your racing drone. In the left-most graph, the horizontal lines represent heat losses, which are dependent only on torque and current, not RPM. The lower torque and current your motor operates at, the lower the heat losses. The graph in the middle shows the maximum power curve originating from the origin. If the motor does not operate along this line, it is operating at less than full power potential. A max power condition is ideal for winning a race, but not for increasing flight time or endurance. Finally, the right-most graph shows the maximum efficiency curve. A motor operating on this line will use it’s battery more efficiently than anywhere else on the graph, thus increasing the flight time and endurance.
When modifying the operating range of your motor, you will be looking at changing either your motor size, propeller size or both. In other words, you will be trying to optimize the load of the motor for its size. An easy way to tell if a motor isn’t efficient is to measure it’s temperature. A motor heating up too much is probably overloaded, AKA it is too small for its load. Furthermore, a motor not warming at all is probably too heavy or too big for its load, thus inefficient in that setup. Your needs will help you determine if you should start by modifying your motor or propeller size first.
When evaluating the performance of a motor, using both theoretical and experimental methods will give you the best understanding of your device. The difference between theoretical and experimental results comes from incorporating theoretical assumptions in your calculations, and also from imperfections in your measuring devices. For example, the ESC isn’t perfect and might sometimes activate at the wrong time. Bearing friction is also not taken into account and the measuring instrument’s precision comes with an expected error.
The theoretical model is a good tool to understand intuitively how a change will affect the motor performance. To confirm your assumptions and optimize your system, you need to perform actual measurements in a systematic way. Motor performance can be improved in several ways and the best way to determine them is to compare theory with test results to get a better understanding of your whole system.