July 6, 2018
Creating internal combustion predictive model for Mitsubishi Motors
Industry: Automotive | Product: pSeven | Company: Mitsubishi Motors Corporation
DATADVANCE constructed a predictive model for Mitsubishi Motors to predict internal combustion pressure model parameters.
The modern automotive market requires manufacturers to balance between increasing customer demands, strict environmental regulations. To meets the regulations, lightweight and good efficiency vehicle are required. But sometimes these negatively affect NVH comfortability. For these interwoven attributes, using the numerical simulation, system modeling, and design space exploration become the best option automotive companies can find an optimal solution to meet all these requirements.
Calculating engine exciting force requires knowing internal combustion pressure at arbitrary operation regimes. And combustion pressure is changed repeatedly every development phase with calibration of control design value. But it needs to build a complex and large-scale engine model. To describe the combustion process, in this case, Mitsubishi Motors used very simple physical model and predictive model with well-known Wiebe function that depends on five internal parameters and polytropic index. The simple engine model is also affected by several operational parameters, so parameters of Wiebe function model are required to adopt such variations. Predictive model can find out Wiebe function parameters at the arbitrary condition and consequently, it gives an accurate combustion pressure calculation in the simple model.
Experimental engine in-cylinder pressure vs. crank angle curves for different RPM
pSeven was used as a powerful and helpful tool to predict combustion model parameters. It allowed creating a single workflow that uses an available small number of experimental data as input, run combustion simulation in Simulink and implement approximation techniques to results. As a first step, optimization of residuals was used to fit the parameters of a combustion model to existing experimental combustion pressure vs. crank angle curves. As the next step, a predictive model was created to predict these parameters at arbitrary regimes using known values, like intake and exhaust manifold pressure, fuel consumption, injection timing, O2 concentration, brake mean effective pressure and RPM.
Multidimensional predictive model of combustion created in pSeven
The created predictive model will be further used in 1D engine simulations via export through m-file or FMI (Functional Mock-up Interface), a tool-independent standard to support both model exchange and co-simulation of dynamic models, in almost any system modeling software. Such predictive models are also very fast in terms of computation, so implementing them in the product development process leads to significant time savings.
Case study of combustion pressure estimation model and NVH combination
About Mitsubishi Motors Corporation
Mitsubishi Motors Corporation is a global automobile company based in Tokyo, Japan, which has a competitive edge in SUVs and pickup trucks, electric and plug-in hybrid vehicles. The company launched the i-MiEV – the first mass-produced electric vehicle in 2009, which was followed by the OUTLANDER PHEV in 2013 – a plug-in hybrid market leader in Japan and Europe. Mitsubishi Motors has 30,000 employees and a global footprint with production facilities in Japan, Thailand, China, Indonesia and Philippines. Models, such as the PAJERO SPORT/MONTERO SPORT, TRITON/L200, and OUTLANDER play a major role in achieving its growth. The global sales volume in the fiscal year 2017 was 1,101,000 units, and the net sales of Mitsubishi Motors for the fiscal year 2017 was 2.19 trillion yen. Mitsubishi Motors is listed on the Tokyo Stock Exchange.