Sustainable vehicle configurations brought to market faster thanks to Modular Energy Management Strategy

90% less greenhouse gas emissions from road traffic

The European Green Deal aims to reduce greenhouse gas emissions from road traffic by 90% by 2050. In addition to road transport, non-road and maritime applications, such as construction and agricultural machinery, must also achieve significant CO2 reductions.

In order to achieve this, we are seeing an increasing variety of drive systems: conventional combustion engines with a sustainable fuel, battery-electric solutions, fuel cells, and also hybrid drive systems. Each application often has a (slightly) different drive system for a low Total Cost of Ownership (TCO) and higher productivity.

However, these vehicles and drive systems must have an efficient energy management system to optimally control components such as the combustion engine, electric motor, and battery. The vehicle controller (VCU) continuously determines the optimal distribution of requested power between consumers and energy sources via an Energy Management Strategy algorithm, depending on the application and environmental conditions.

Time-consuming R&D

However, developing such energy management systems for each vehicle, for every application, has become a time-consuming and costly process due to the multitude of drive and energy components.

Jan-Willem Sangers, Business Developer Sustainable Vehicles at TNO: 'This is especially evident in the development of non-road mobile machinery, such as excavators, wheel loaders, and tractors. For each task, there is a specific variant with an optimal configuration for that application. As a result, there are often many different configurations within a product, each with an individual combination of components. Investigating and determining an optimal Energy Management Strategy for each variant, in every configuration, places a significant demand on a manufacturer’s R&D capacity.'

TNO contributes to this challenge with the development of a Modular Energy Management Strategy (MEMS). Paul Mentink, Senior Research Scientist Integrator Powertrains at TNO: 'It is a complete Vehicle Energy Management algorithm that can, in principle, perform energy management for any type of drive system and ensure an optimal distribution between energy consumers and energy storage.'

MEMS in practice

Traditionally, an R&D process for each powertrain configuration, or topology, goes through the same steps, Mentink explains. 'For a new product, say a tractor, this process begins with inventorying the new components. Think of innovative batteries, new electric machines, and combustion engines. Then, the possible topologies are determined: these are the different combinations of components we want to investigate. Ultimately, this results in one topology that meets all the requirements for that specific application.

The unique aspect of the MEMS algorithm is its modular structure. This allows us to compare and calculate many different combinations in a short time. The algorithm maintains the same structure for each configuration, enabling engineers to effortlessly exchange different powertrain components and try out topologies. MEMS allows for a fair comparison between different configurations, as each topology is controlled by an optimal regulator.'

TNO has calculated that this approach saves about 20 percent of time per topology in the development phase compared to conventional algorithms. With multiple configurations and reuse of components, there is an additional saving, as components do not need to be recalibrated.