Design of NASA Robotic MARS Helicopter Using Matlab Simulink

This example shows how to use Simscape™ Electrical™ to model a helicopter with coaxial rotors suitable to fly on Mars.

This helicopter takes inspiration from Ingenuity, the robotic helicopter developed by NASA, which accomplished the first powered flight on another planet.

References:
https://in.mathworks.com/help/physmod/sps/ug/mars-helicopter-system.html?s_eid=psm_ml&source=15308

Withrow, S., Johnson, W., Young, L. A., Cummings, H., Balaram, J., & Tzanetos, T. (2020). “An Advanced Mars Helicopter Design”. ASCEND 2020. doi:10.2514/6.2020-4028 

Pipenberg, B. T., Keennon, M., Tyler, J., Hibbs, B., Langberg, S., Balaram, J. (Bob), Pempejian, J. (2019). “Design and Fabrication of the Mars Helicopter Rotor, Airframe, and Landing Gear Systems”. AIAA Scitech 2019 Forum. doi:10.2514/6.2019-0620

Balaram, B., Canham, T., Duncan, C., Grip, H. F., Johnson, W., Maki, J., Zhu, D. (2018). “Mars Helicopter Technology Demonstrator”. 2018 AIAA Atmospheric Flight Mechanics Conference. doi:10.2514/6.2018-0023

Contents
Introduction – MARS Helicopter Technology
Introduction - Mars Helicopter System-Level Design
Simulink Model – NASA Robotic MARS Helicopter
Model Overview & Battery Pack Variant
Flight Control System & Command Dashboard subsystem
Simulation & Result Analysis:
Altitude and Battery Cell Temperatures
Flight Duration Vs Number of Battery Cells

Introduction – MARS Helicopter Technology

The Mars Helicopter is an autonomous 1.8 kg co-axial, counter-rotating rotorcraft baselined to fly on the Mars 2020 mission to demonstrate aerial mobility on the surface of Mars.

The rotor system consisting of the rotor blades, hub mechanism, propulsion motors, swashplates and linkages, control servos, and primary helicopter structure.

The landing gear system consisting of 4 deployable legs, landing feet, and suspension mechanisms.

Auxiliary structures, including the structural elements of the Helicopter Warm Electronics Box (HWEB) that encloses the electronic core module (ECM) and battery, and the solar array substrate that serves as the structural element of the solar panel system.

The solar array located above the blades is used to recharge the helicopter batteries during the day to provide power for flight operations and overnight thermal survival.

This example shows how to use Simscape™ Electrical™ to model a helicopter with coaxial rotors suitable to fly on Mars.

This helicopter takes inspiration from Ingenuity, the robotic helicopter developed by NASA, which accomplished the first powered flight on another planet.

To control the helicopter altitude interactively, can use the blocks in the Command Dashboard subsystem.

The helicopter model comprises
Solar Panel,
Battery Pack,
Heater,
Motor & Drive,
Two gearboxes
Two contra-rotating coaxial rotors,
1D mechanical model of the gravity, drag, mass, and ground contact forces.

Click here to download the model:
2021a version:
https://drive.google.com/file/d/1M8IaiPS18JpqkPC8Qe4U7P4x1x_j4Q4c/view?usp=sharing

021b version
https://drive.google.com/file/d/1Lox1X363nFNrMaLXKTghBR7X4LhpONfu/view?usp=sharing

Modeling & FFT analysis on PCC- Inverter-based Micro grid with Droop Control Technique Using Matlab

This example shows the islanded operation of an inverter-based microgrid using droop control technique.

With the droop control technique, PLL are not required to achieve system-wide synchronization because all inverters reach the same frequency.

The microgrid consists of three parallel inverters subsystems, with power ratings of 500 kW, 300 kW and 200 kW respectively, connected to the PCC (Point-of-Common-Coupling) bus.A dynamic load model is used to dynamically change the microgrid total load.

The Microgrid Supervisory Control system, when enabled, modifies the inverters P/F and Q/V droop set points in order to bring back the microgrid frequency and voltage at their nominal values (60 Hz and 600 Volts respectively).

The example illustrate the operation of an inverter-based microgrid disconnected from the main grid (islanded mode), using the droop control technique.

Each inverter subsystem contains a three-phase two-level power converter, an LC filter, a 480/600V transformer as well as an ideal DC source to represent the DC link of a typical renewable energy generation system (such as PV array, wind turbine, battery energy storage system).

Each subsystem also includes a control system and a PWM generator feeding the inverter.

The analysis is based on the frequency reference that capable in generating the output of voltage and current as well as the equality of load power sharing when a load disturbance occurs in the parallel-connected inverters.

The FFT Analyzer app allows we to perform Fourier analysis of simulation data and provides access to all the simulation data that are defined as structure-with-time variables in our workspace.

The app displays the spectrum as a bar graph or as a list in percentages relative to a base value or to the DC component of the signal.

To Open the FFT Analyzer App:
MATLAB command prompt:
Enter  powerFFT

Analysis :
At 1 s, the total micro grid load is increased from 450kW/100kvar to 850kW/200kvar. At 3 s, droop control is enabled on all inverters.
We can see that the micro grid load is now shared equally among the three inverters.
At 5 s, the supervisory control is enabled. The frequency is then being slowly increased to 60Hz and the line voltage to 600V.
The droop P/F is set to 1%, meaning that microgrid frequency is allowed to vary from 60.3 Hz (inverter produces no active power) to 59.7 Hz (inverter produces its nominal active power).

The droop Q/V is set to 4%, meaning that the microgrid voltage at the PCC bus is allowed to vary from 612 Vrms (inverter produces its full inductive power) to 588 Vrms (inverter produces its full capacitive power). Note that Qmax is specified as half of the nominal active power Pnom.

To demonstrate the impact of the inverters PWM carrier’s initial phase on the PCC bus voltage harmonic content, first open the FFT Analyzer App to perform an FFT analysis of the PCC phase A bus voltage.

In the App, set the Structure with time parameter to PCC , the Signal parameter to V_PCC, and the Dimension parameter to 1 to analyze the PCC phase A bus voltage. Set the Zoom on parameter to FFT window , the Start time parameter to 7.9 , and the Max frequency parameter to 7000. Click Compute FFT. In the FFT plot, the maximum harmonic occurs around the switching frequency (2700 Hz) and is close to 2%.

Now, double-click on the Inverter 2 (300 kW) subsystem and change the Carrier initial phase parameter to -90 degrees. Rerun the simulation and again, perform an FFT analysis on the PCC phase A voltage. We should see that this new carrier phase setting significantly reduces the harmonic content around the switching frequency (2700 Hz). This is due to the fact that Inverter 1 carrier phase is set to +90, so switching harmonics are then partially canceled.

Click here to download the file:
2020a version:
https://drive.google.com/file/d/15A6V1SPbP9hXL9zLO7j4bvgvJiYNwepl/view?usp=sharing
2021a version:
https://drive.google.com/file/d/1t6WCRfMjqF6ku2x04iCJ0nJmgFv5dQPZ/view?usp=sharing
2021b version:
https://drive.google.com/file/d/10sDfAa9AWhWMGn00mkRRgnnyEARy30hQ/view?usp=sharing

Modeling & Analysis of PEM Fuel Cell System Using Matlab Simulink

This example shows Modeling & Analysis of proton exchange membrane (PEM) fuel cell stack system to set up 1) Electrical Load : A) drive cycles, B) step C)Ramp 2)Power Produced & Consumed By The System 3) Plot the fuel cell I V curve, Efficiency & Utilization and Temperature in Fuel Cell system 4) Hydrogen consumed by the fuel cell.

• This example shows how to model a proton exchange membrane (PEM) fuel cell stack with a custom Simscape block.
• The PEM fuel cell generates electrical power by consuming hydrogen and oxygen and producing water vapor.
• The custom block represents the membrane electrode assembly (MEA) and is connected two separate moist air networks: one for the Anode Gas Flow and one for the Cathode gas flow.
• The two moist air networks represents different gas mixtures.
• The anode network consists of nitrogen (N2), water vapor (H2O), and hydrogen (H2), representing the fuel.
• The hydrogen is stored in the fuel tank at 70 MPa.
• A pressure-reducing valve releases hydrogen to the fuel cell stack at around 0.16 MPa.
• Unconsumed hydrogen is recirculated back to the stack.
• The cathode network consists of nitrogen (N2), water vapor (H2O), and oxygen (O2), representing air from the environment.
• A compressor brings air to the fuel cell stack at a controlled rate to ensure that the fuel cell is not starved of oxygen.
• A back pressure relief valve maintains a pressure of around 0.16 MPa in the stack and vents the exhaust to the environment.
• The temperature and relative humidity in the fuel cell stack must be maintained at an optimal level to ensure efficient operation under various loading conditions.
• Higher temperatures increase thermal efficiency but reduce relative humidity, which causes higher membrane resistance.
• Therefore, in this model, the fuel cell stack temperature is kept at 80 degC.
• The cooling system circulates coolant between the cells to absorb heat and rejects it to the environment via the radiator.
• The humidifers saturate the gas with water vapor to keep the membrane hydrated and minimize electrical resistance.
• This plot shows the current-voltage (I-V) curve of a fuel cell in the stack.
• As the current ramps up, an initial drop in voltage occurs due to electrode activation losses, followed by a gradual decrease in voltage due to Ohmic resistances.
• Near maximum current, a sharp drop in voltage occurs due to gas-transport-related losses.
• This plot also shows the power produced by the cell.
• When the ramp scenario is selected, the power increases until a maximum power output, then decreases due to the high losses near maximum current.
• Click here to download the Simulink files: 2021a version:

https://drive.google.com/file/d/1XTnG4zOll1MR58gy_GU7F0K60uUBPCOh/view?usp=sharing

2020a version: https://drive.google.com/file/d/1VigTbfawAmigpxoK5eAka8gx-GU_UBN6/view?usp=sharing

2019a version: https://drive.google.com/file/d/1eGiWLTkdz0lS-o2odx1D8OCXRcOQuEMM/view?usp=sharing

2018a version: https://drive.google.com/file/d/1GReipArHs_fhwCMPjfkIm1AuS1BNTs6Y/view?usp=sharing Kindly Subscribe My YouTube Channel... Please like, share and worthy comments on My Videos 🙏 Please click the below links to Subscribe/Join & View my Videos https: //www.youtube.com/c/DrMSivakumar Telegram : t.me/Dr_MSivakumar website : drmsivakumar78.blogspot.com

Part 1_ Design an Energy System for a Hydrogen-Based Electric vehicle Using Matlab Simulink

This example shows Fuel Cell Electric Vehicle Model with a Motor-Generator, Battery, Direct-Drive Transmission, and Associated Powertrain Control Algorithms.

FCEVs are equipped with other advanced technologies to increase efficiency, such as regenerative braking systems that capture the energy lost during braking and store it in a battery.

This example shows how to create an Fuel Cell electric vehicle reference application project using Matlab.

Run the following command to create and open a working copy of the project files: >>autoblkFCEvStart According to the simulation results including FTP75 and WLTP cycles, it was understood that vehicle speed and cycle speed were the same.

Simulation Result: Displays vehicle-level performance, battery state of charge (SOC), and equivalent fuel economy results that are useful for powertrain matching and component selection analysis. At this point, it is concluded that the energy consumption data obtained from the model is also correct.

Part 2 _ Modeling of an Fuel Cell Electric Vehicle with MATLAB/Simulink

This example shows how to create an Fuel Cell electric vehicle reference application project using Matlab.

Contents

Introduction - Fuel Cell Electric Vehicle

• Fuel cell electric vehicles (FCEVs) are powered by hydrogen.
• They are more efficient than conventional internal combustion engine vehicles and produce no tailpipe emissions, they only emit water vapor and warm air.
• The U.S. Department of Energy leads research efforts to make hydrogen-powered vehicles an affordable, environmentally friendly, and safe transportation option.
• Powertrain Blockset & Simscape Driveline
• Built-in Controller Models
• Powertrain Blockset Blocks for Vehicle design
• Powertrain Design tradeoff studies
• Modeling of an Fuel Cell Electric Vehicle with MATLAB/Simulink
• Sample Output Comparison with Different Drive Cycles

Simulation & Result Analysis : Displays vehicle-level performance, battery state of charge (SOC), and equivalent fuel economy results that are useful for powertrain matching and component selection analysis. FCEVs use a propulsion system similar to that of electric vehicles, where energy stored as hydrogen is converted to electricity by the fuel cell. Unlike conventional internal combustion engine vehicles, these vehicles produce no harmful tailpipe emissions.

FCEVs are fueled with pure hydrogen gas stored in a tank on the vehicle. Similar to conventional internal combustion engine vehicles, they can fuel in less than 4 minutes and have a driving range over 300 miles. Motor torque arbitration and power management: 1) Implements a regenerative braking algorithm for the traction motor to recover the maximum amount of kinetic energy from the vehicle. 2) Implements a power management algorithm that ensures the battery dynamic discharge and charge power limits are not exceeded. 3) The algorithm outputs the dynamic discharge and charge power limits as functions of battery state of charge (SOC). 4) Implements a virtual battery management system. Click here to get the Simulink File: https://drive.google.com/file/d/1ph75ejjGFlWFF4EkC8pV7UWzLyIJpuPZ/view?usp=sharing Click here to get the Whole Project File: https://drive.google.com/file/d/1SuXjtS_-ar61tPWd3RWKSXoZbgqiG5D7/view?usp=sharing