Project Honda Research Institute

Simulations enable Honda to calculate costs, emissions and primary power balances of different renewable and conventional system configurations.

The Honda Research Institute Europe uses SimulationX for the research of intelligent energy management systems.

The task at hand

Analysis and optimization of building layouts

In Germany, Japan, and other countries, the networks of electricity production, transmission, storage and usage are being substantially modified due to growing concerns on climate change, increasing fossil fuel prizes and the phase-out of nuclear power after the Fukushima accident. Renewable sources of energy have to replace conventional (fossil and nuclear) sources and societies need to reduce their energy demand in areas, such as production, households and mobility. In this context, Honda has unveiled the Honda Smart Home System (HSHS) in Japan's Saitama prefecture near Tokyo back in 2012. The HSHS combines energy production through photovoltaic (PV) and micro combined heat and power generators (mCHP) with battery storage and e-mobility devices like electric vehicles or fuel cell cars. The operation of the house is controlled and coordinated by a central smart control unit, the Smart e-Mix Manager (SeMM). This new generation of eco-friendly buildings is able to handle its inhabitants’ energy demand autonomously. However, developing renewable energy sources while ensuring save supply and affordability pose a huge challenge. Green buildings such as the HSHS must be durable, efficient and cost-effective. Thus, the main problem is that renewable energy sources such as wind and solar energy cannot be used in the same way as conventional resources due to their fluctuating availability. That is why smart systems for designing, analyzing and optimizing building layouts are vital.

Such tools can calculate and balance the demand and the production to assess energy saving potentials prior to the installation of the actual energy system. In order to understand the interaction of the different modules with the home's owners and the environment, a detailed simulation of the HSHS was needed. For Honda as a mobility company, a building-centered simulation environment was not sufficient since the company aims at providing a green and affordable mobility by integrating cars and home appliances. To study how electrified mobility and smart home systems can interact in an optimal way, the Honda Research Institute Europe and EA Systems developed a model of a smart home system with an attached plugin hybrid electric vehicle (PHEV). The simulation uses the ‘Green Building’ Library of the system simulation software SimulationX. The versatile tool helps engineers answer the above mentioned questions and calculate the optimal use of energy resources and decentralized energy storage. With this interdisciplinary simulation software, engineers design, analyze and create virtual prototypes of technical components and complex systems of energy efficient buildings on a single software platform. The software has a straightforward user interface and comes with ready-to-use elements based on real-world data.

The solution

Green Building library in SimulationX

In the simulation system, a standard single-family home with three zones (ground floor, upper floor, attic) and a heating system for the first two zones were modeled. The house uses a PV system for electricity and an mCHP for combined heat and electricity production. To provide enough heat even under extreme weather conditions, a conventional heat boiler system was added. The house was also connected to the electricity grid and uses an in-house battery to store electricity. Finally, the engineers modeled the house owners' mobility demands via a vehicle that runs approximately 8000 km/year or 30 km/day. The car was assumed to be docked to the house for certain periods of time when recharging is possible. In a pre-processing step, the average fuel and energy demand of the car was computed for the specific driving demands. These averages are used in the actual simulation of the smart home system. This approach was chosen due to the different time-scales of car and house dynamics. The model system could also be instantiated in different variations including a conventional system without PV and mCHP, but with a conventional combustion engine for mobility. It was therefore possible to compare different system configurations in terms of their economic merits, environmental footprint, provided comfort and a variety of other aspects. The operation of the system depended on many factors two of which, the most important ones, were user profiles and environmental conditions (e.g. weather). Both factors may change from one day to the next and vary for different locations.

To deal with these variations, Honda decided to stick to one specific location for all simulations (i.e. Berlin in this case) and simulated an entire year in order to even out seasonal changes. This first model system required several days of simulation time despite a high simulation speed. To speed up the simulation, the engineers employed the reference day method which simulates a small number of prototypical reference days and weights their relative occurrence over the course of one year. As a result, simulation time could be reduced to a couple of hours on a single computer. Environmental data, such as climate data, user profiles (e.g. daily electricity demand) and driving patterns, could be specified using simple Excel sheets. The simulator provided its output data also in Excel format in order to make data analysis and visualization easier. This approach greatly simplifies adapting the model to other locations or usage patterns.

The benefits

Simulating vehicle and building systems for intelligent energy management on just one software platform

Using the simulator, Hondas’ engineers computed costs, emission levels and primary energy balances of different renewable and conventional energy configurations. Although renewable configurations with PV, mCHP and PHEV were more expensive, the data showed that they also result in substantially lower CO2 emissions. Moreover, a simple charging strategy was found for the electric vehicle using the battery which in turn is charged by the PV system to provide a high share of 'green' (CO2 free) electricity for mobility. The exact percentage strongly depended on the size of the battery that was installed in the HSHS. Using a parameter scan for battery size, Honda could identify the battery’s optimal dimensions.

Honda also uses the simulator to continuously perform automatic optimizations of the system configuration considering multiple optimization criteria through so-called Evolutionary Many-Objective Optimization (EMAO) algorithms. The goal is to analyze the potential of the system for different configurations and to understand the correlations between the different objectives. One of the main benefits of using evolutionary algorithms is easy parallelization reducing the time needed for optimization a great deal. In cooperation with ITI and EA Systems Dresden, Honda engineers simplified and improved the model system for reduced runtimes resulting in much shorter average simulation times.

Simulation in energy technology

The multiphysics simulation software SimulationX is available to beginners with several pre-configured application packages for various tasks in energy engineering. Learn more!

SimulationX for beginners