Hardware-in-the-Loop (HIL) test platform for planetary rovers was designed, fabricated and tested in the present work. The ability for planetary rover designers and mission planners to estimate the rover’s performance through software simulation is crucial. HIL testing can further the benefits of software simulations by allowing designers to incorporate hardware components within traditionally pure software simulations. This provides more accurate performance results without having access to all hardware components, as would be required for a full prototype testing. The test platform is designed with complete modularity such that different types of tests can be performed for varying types of planetary rovers and in different environments. For demonstrating the operation of the test platform, however, the power system operation of a solar powered rover was examined. The system consists of solar panels, a solar charge controller, a battery, a DC/DC converter, a DC motor and a flywheel. In addition, a lighting system was designed to simulate the solar radiation conditions solar panels would experience throughout a typical day. On the software side, a library of component models was developed within MapleSim and model parameters were tuned to match the hardware on the test bench. A program was developed for real-time simulations within Labview allowing communication between hardware components and software models. This program consists of all the component models, hardware controls and data acquisitioning. The GUI of this program allows users to select which component is to be tested and which component is to be simulated, change model parameters as well as see real time sensor measurements for each component. A signal scaling technique based on non-dimensionalization is also presented, which can be used in an HIL application for obtain scaling factors to ensure dynamic similarity between two systems. A demonstration of power estimation was performed using the pure software model simulations as well as the pure hardware testing. Hardware components were then added into the software simulation progressively with results showing better accuracy as hardware is added. The rover’s power flow was also estimated under different load conditions and seasonal variation. These simulations clearly demonstrate the effectiveness of an HIL platform for testing a rover’s hardware performance.

Hardware-in-the-Loop (HIL) test platform for planetary rovers was designed, fabricated and tested in the present work. The ability for planetary rover designers and mission planners to estimate the rover’s performance through software simulation is crucial. HIL testing can further the benefits of software simulations by allowing designers to incorporate hardware components within traditionally pure software simulations. This provides more accurate performance results without having access to all hardware components, as would be required for a full prototype testing. The test platform is designed with complete modularity such that different types of tests can be performed for varying types of planetary rovers and in different environments. For demonstrating the operation of the test platform, however, the power system operation of a solar powered rover was examined. The system consists of solar panels, a solar charge controller, a battery, a DC/DC converter, a DC motor and a flywheel. In addition, a lighting system was designed to simulate the solar radiation conditions solar panels would experience throughout a typical day. On the software side, a library of component models was developed within MapleSim and model parameters were tuned to match the hardware on the test bench. A program was developed for real-time simulations within Labview allowing communication between hardware components and software models. This program consists of all the component models, hardware controls and data acquisitioning. The GUI of this program allows users to select which component is to be tested and which component is to be simulated, change model parameters as well as see real time sensor measurements for each component. A signal scaling technique based on non-dimensionalization is also presented, which can be used in an HIL application for obtain scaling factors to ensure dynamic similarity between two systems. A demonstration of power estimation was performed using the pure software model simulations as well as the pure hardware testing. Hardware components were then added into the software simulation progressively with results showing better accuracy as hardware is added. The rover’s power flow was also estimated under different load conditions and seasonal variation. These simulations clearly demonstrate the effectiveness of an HIL platform for testing a rover’s hardware performance.

<p dir="ltr">The automotive industry has witnessed a significant transformation in recent years, largely driven by the emergence of electric powertrains. These systems offer a cleaner and more efficient alternative to traditional internal combustion engines, marking a pivotal shift towards sustainability in the transportation sector. At the heart of electric vehicles (EVs) lies the powertrain, a complex assembly of components tasked with converting electrical energy into mechanical power to propel the vehicle. In the context of electric race cars, the design and optimization of the powertrain are of utmost importance to achieve high performance on the track. The powertrain typically consists of four major components: the motor, inverter, battery, and gearbox. Each of these components plays a critical role in ensuring the efficient conversion and utilization of electrical energy to drive the vehicle forward. The process of designing an electric race car powertrain begins with a thorough understanding and explanation of each component's function and contribution to overall performance. This foundational understanding serves as the basis for subsequent analysis and optimization efforts. Central to the design process is the selection and configuration of the motor and battery, two key components that heavily influence the vehicle's performance characteristics. To facilitate this decision-making process, engineers leverage specialized software tools such as OptimumLap, MATLAB, and Simulink. OptimumLap allows engineers to input relevant parameters of the race car, such as its drag coefficient and frontal area, to gain insights into its aerodynamic performance. By conducting simulations on specific race tracks, such as the Adelaide circuit, engineers can generate valuable data representing the vehicle's performance in terms of lap times and speed. MATLAB's Grabit tool is then utilized to extract velocity data from the simulation results, providing crucial input for further analysis. This data is used to create a comprehensive table of values representing the vehicle's velocity profile under different conditions. Finally, engineers develop a Simulink model to simulate the operation of the electric powertrain under various scenarios. This model allows for the extraction of critical performance metrics and parameters, enabling engineers to optimize the motor and battery configuration to meet the specific requirements and constraints of the race car.</p>