Internship: Research and Validation of Battery SoC and SoH Estimation for Autonomous Robots

Electrification plays an increasingly important role in Lely autonomous robot systems. Battery behaviour, lifetime, cost and diagnostic reliability are key topics within this domain and directly influence robot availability and future product choices. Within this internship you will contribute to the research and validation of practical methods to estimate the state of charge (SoC) and state of health (SoH) of Lead Carbon batteries used in robot applications.

The assignment focuses on comparing estimation approaches across different system cost and complexity levels. You will start from a very low-cost setup, where there is no battery communication and only limited or no direct battery measurements available. From there, you will evaluate increasingly capable solutions, up to a battery system with a cell balancer or battery management electronics that can communicate battery data to the robot.

The goal is to determine which SoC and SoH estimation approach is technically suitable, economically sensible and realistic to integrate in one of our robots. The assignment combines theory, data analysis and experimental validation.

Part 1 - Analysis of SoC and SoH estimation methods

You start with a structured comparison of battery estimation methods based on literature research, supplier information and technical documentation. The analysis should include both low-complexity and higher-complexity options. Topics you investigate include:

• State-of-charge estimation by voltage, current integration / coulomb counting and model-based approaches
• State-of-health indicators such as available capacity, internal resistance, voltage behaviour and ageing trends
• Impact of limited sensing: no communication, limited measurements or indirect robot-side measurements
• Value of additional electronics such as a cell balancer, BMS or communication interface
• Cost, complexity, robustness and integration effort for each method
• Expected suitability for lead-carbon batteries and other relevant robot battery options

The outcome of this part is a technically supported overview of the possible estimation methods, including their strengths, limitations and realistic usability in a robot environment.

Part 2 - Experimental validation and comparison

Next to the theoretical comparison, you validate selected methods experimentally. You will set up and execute battery tests that allow the different SoC and SoH estimation approaches to be compared using real measurement data. The experimental work may include:

• Charge and discharge cycles to characterise battery behaviour over time
• Testing under different temperature conditions, using a temperature cell or climate chamber where available
• Comparison of new batteries with aged batteries from the field
• Data logging and analysis of voltage, current, capacity, efficiency and temperature-related behavior
• Validation of estimation accuracy versus measured reference data

You will analyze the recorded data and compare the practical results with the theoretical expectations. This should lead to a clear recommendation on which estimation approach gives the best balance between cost, complexity and diagnostic value for a robot application.

Part 3 - Recommendation for robot application

Based on the research and experiments, you translate the findings to a practical recommendation for use in a Lely robot. The recommendation should explain what can be achieved with a very low-cost system, where extra measurements or communication become valuable and which solution is most likely to fit current or future robot platforms. Depending on the planning and available hardware, the assignment may also include a small proof of concept in which the chosen method is implemented or demonstrated using Python-based data processing, a test setup or robot-relevant measurement data.

What is your experience?

We are looking for an enthusiastic HBO student with an interest in electronics, batteries, data analysis and Autonomous Mobile Robots. You recognize yourself in the following:

• Interest in battery technology, diagnostics and energy storage
• Affinity with electronics, measurement systems, electric drive systems and practical prototyping
• Comfortable setting up experimental test equipment
• Experience or interest in communication protocols such as CAN and Modbus for data acquisition and diagnostics
• Analytical mindset and curiosity to validate assumptions experimentally
• Able to work independently while actively seeking collaboration
• Good communication skills in English

What you can expect from us

At Lely, we offer you an educational and dynamic internship experience at one of the most innovative organizations in the Netherlands. You’ll become part of a driven team and have plenty of opportunities to further develop your talents.

• An international working environment
• An internship allowance of €650 per month based on a 40-hour work week
• A student apartment if your commute is too long