Multidisciplinary Design Optimization for a Solar-Powered Exploration Rover Considering the Restricted Power Requirement
Abstract
1. Introduction
2. Modeling of the Operational Environment
2.1. Power Acquisition Model
2.2. Modeling of Terrain Characteristics in Lunar Simulant
2.2.1. Pressure-Sinkage Relationship Associated with Normal Stress Component
2.2.2. Mohr–Coulomb Failure Criterion/Janosi–Hanamoto Model Associated with Shear Stress Component
3. Multi-Body Dynamics Simulation Tool Based on the Wheel-terrain Interaction Model
3.1. Wheel-Terrain Interaction Model
3.2. MBD Simulation Tool Based on Wheel-Terrain Interaction
number of limbs, | |
inertia matrices for the entire system composed by the inertia property of each body | |
position/orientation of the base body, | |
articulated joint angles, | |
non-linear velocity-dependent term, | |
gravity term, | |
forces exerted on the base body, | |
joint articulated torque, | |
external forces/torques acting on the wheel, | |
[38]. |
Algorithm 1 Multi-Body Dynamics Simulation Based on the Wheel-Terrain Interaction Model |
|
4. Multi-Objective Design Optimization Based on Operational Environment in Accordance with the Target Landing Site
4.1. System-Level Requirements
4.2. Wheel Parameter Sensitivity Analysis via Developed MBD Simulation Tool
4.3. Multi-Objective Wheel Design Optimization
4.3.1. Objective Function
4.3.2. Constraint Condition
4.3.3. Optimization Algorithm
4.3.4. Optimization Procedure
4.3.5. Results of Multi-Objective Optimization Problem with NSGA-II
5. Performance Evaluation of Optimal Design Results
5.1. Case Study: Scenario-Based Dynamic Analysis
5.1.1. Rover Model and MBD Simulation Procedure
5.1.2. Case Study: Driving over Flat Deformable Terrain
5.1.3. Case Study: Climbing Slope at 2.2° Inclined Terrain
5.1.4. Case Study: Traversing on 2.2° Side Slope
5.2. Experimental Verification
5.2.1. Single Wheel Testbed and Experimental Procedure
5.2.2. Results of Experimental Verification
5.2.3. Discussion
6. Conclusions
- The modeling of solar power acquisition and terrain characteristics on the Moon for predicting the operational environment of the exploration rover is described.
- An MBD simulation tool based on the rover wheel-terrain interaction model, which can deal with the longitudinal/lateral dynamic behavior of exploration rover with the path following the controller on a given digital elevation model map, is developed.
- Via sensitivity analysis with regard to the wheel geometry parameters, the dominant design parameter is selected, and a multi-objective wheel design optimization method integrating the developed simulation environments and NSGA-II is created over various dynamic states. With the use of MOOP based on the NSGA-II method, an optimal design point that considers both tractive coefficient and energy consumption is obtained.
- Numerical/experimental verification using a single wheel testbed were conducted to convincingly validate the derived optimization results and simulation environment. Compared to the comparative group, the optimized design was enhanced by −71% in terms of the sinkage (associated with the immobility), +398% in terms of tractive coefficient (associated with the tractive capability), and −57.9% in terms of the driving resistance torque (associated with power condition).
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Parameter | Description | Unit | Value |
---|---|---|---|
relative density | |||
sinkage exponent | |||
pressure-sinkage modulus | |||
cohesion | |||
friction angle | |||
shear deformation modulus |
Lunokhod | Yutu | Polaris (Google Lunar X Prize) | Moonraker (Google Lunar X Prize) | Amalia (Google Lunar X Prize) | |
---|---|---|---|---|---|
Mass (kg) | 840 | 140 | 149 | 8.424 | 30.9 |
Mission location (-) | Sea of Rains (38.24 35.01 | Lacus Mortis (44.95 26.61 | Moon’s Pole | Marius Hills (13.0 306.2 | Lunar Equatorial |
Mission timeline (day) | 116 | 90 | 14 | ||
Thermal control (-) | Yes | Yes | Yes | ||
Considered temperature range (℃) | −180 to +50 | to +120 | to +200 | −150 to +150 | |
Power source (-) | Solar | Solar + Pu238 | Solar | Solar | Solar |
Solar cell area ( | 4 | 3.6 | 0.22 | 0.36 or more | |
Power consumption (W) | 50 | 30 | 250 | 24.2 | 73.8 |
Number of wheels (-) | 8 | 6 | 4 | 4 | 4 |
Suspension type (-) | Custom-machined rocker-bogie | Rocker-bogie | Passive rocker | Roll axis swing arms | Roll axis swing arms |
Maximum speed (m/s) | 0.22 | 0.056 | 0.41 | 0.045 | 0.014 |
Distance (km) | 39 | 0.1 |
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Kim, K.-J.; Yu, K.-H. Multidisciplinary Design Optimization for a Solar-Powered Exploration Rover Considering the Restricted Power Requirement. Energies 2020, 13, 6652. https://doi.org/10.3390/en13246652
Kim K-J, Yu K-H. Multidisciplinary Design Optimization for a Solar-Powered Exploration Rover Considering the Restricted Power Requirement. Energies. 2020; 13(24):6652. https://doi.org/10.3390/en13246652
Chicago/Turabian StyleKim, Kun-Jung, and Kee-Ho Yu. 2020. "Multidisciplinary Design Optimization for a Solar-Powered Exploration Rover Considering the Restricted Power Requirement" Energies 13, no. 24: 6652. https://doi.org/10.3390/en13246652
APA StyleKim, K.-J., & Yu, K.-H. (2020). Multidisciplinary Design Optimization for a Solar-Powered Exploration Rover Considering the Restricted Power Requirement. Energies, 13(24), 6652. https://doi.org/10.3390/en13246652