Electrification is gaining momentum in many industries and is driving independence from fossil fuel-based technologies.
With the use of power electronics, batteries and electrical machines of all sizes, it has become commonplace to use a growing number of embedded systеms for control and regulation.
How can engineers design such complex systеms, iterate quickly and validate their designs along the way?
For many developers in industries like renewable energy, mechatronics and transportation, the answer is model-based design.
Integration of systеm design and component development
Progressive electrification presents two challenges: the development of individual components and the optimisation of the overall systеm.
In traditional component development, requirements and interfaces are clearly defined.
The aim is to implement these components quickly and efficiently, often using model-based design.
However, the true complexity only unfolds in the systеm-wide optimisation, which includes not only individual vehicle components, but also the interaction of the vehicle, charging infrastructure and energy generation.
The development of systеms and components can no longer be viewed separately; instead, they must be interlinked.
Electrification therefore crosses domain boundaries and different technologies.
Looking at the systеm as a whole helps to define requirements and develop a deeper understanding of component boundaries.
A comprehensive systеm design makes it possible to integrate the different requirements of manufacturers and hardware platforms and to make a manufacturer-independent hardware selection.
Development of embedded systеms independent of hardware
In addition to efficient systеm modeling, model-based design enables hardware-independent algorithm development: the algorithm of a systеm that is implemented on an embedded systеm can be developed and verified independently of the hardware platform.
This enables the integration of controllers as components that do not yet have to be implemented as specific hardware in the model.
Only in the second step is the algorithm implemented on a specific hardware platform with the help of hardware support packages.
These support automated code generation and virtual hardware-in-the-loop simulation.
This approach is already widely used in the automotive industry.
The move towards battery electric vehicles (BEV) and autonomous driving (AD) is leading to a growing need for new electrical/electronic (E/E) architectures, increased computing power and increasingly complex algorithms.
In addition, recent disruptions in the semiconductor automotive supply chain have highlighted the importance of semiconductors and the need for cross-platform flexibility.
Artificial intelligence in electrification
In many respects, the use of artificial intelligence (AI) is setting new standards in the further development of electrification.
For example, AI methods that enable the creation of models for physical components or systеms significantly accelerate the simulation process while mapping the essential behaviour of the systеm.
The integration of AI models into validation and testing also offers advantages.
The development of virtual sensor systеms using AI is another innovative field.
These provide critical signals for the control of electrical systеms without recurring material costs or maintenance.
AI tools also enable the measurement of variables that are difficult to physically measure, such as state-of-charge or state-of-health within a battery management systеm (BMS).
The creation of physics-based models and the generation of synthetic data for the training of such sensors are crucial.
Such models can be directly integrated into systеm models for validation.
AI-based approaches are also used for the development of control algorithms in non-linear systеms, whereby models can be trained against simulated environments and integrated into simulation-based verifications.
In the field of energy forecasting, AI applications help to predict the power supply, demand and pricing more precisely, which leads to a reduction in uncertainties in electricity grid operations.
Cybersecurity in systеm development
The increasing networking of electrical systеms also requires comprehensive consideration of cybersecurity to prevent cyberattacks and ensure the security of the infrastructure.
Innovative approaches and the integration of security aspects in all phases of systеm development are required here.
Cybersecurity must be considered at every stage of systеm development, starting with systеm simulation and requirements engineering.
Fortunately, the importance of cybersecurity is already being underpinned by the first set of rules, standards and regulations.
It is to be expected that legal regulations in this area will continue to increase.
During implementation, the vulnerabilities identified in the systеm design must be secured by secure programming practices.
Programming rules and robustness play a decisive role here.
Solution strategies for an electrified future
On the way to a revolutionary, electrified future, it is the integrated solutions mentioned above that will enable fast, efficient and safe implementation.
Model-based design and AI are becoming pillars of development that not only overcome the boundaries between different technologies and manufacturers, but also ensure the sustainable and safe operation of electrical systеms.
With these tools and methods, engineers and developers are ideally equipped to drive electrification forward and set the course for a more environmentally friendly and technologically intelligent world.
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