Applying Optimization Techniques to control hybrid systems Engines (ATOM)

Programa de apoyo I+D+I UPV. 2012.
This project aims to advance in the optimal control of hybrid vehicles. To achieve this goal, the following objectives are set:
  • Developing an engine model capable of integrating the effect of temperature variation on engine emissions and consumption in a hybrid system. In this project we used average values ​​models (MVEM). A part of the research team has extensive experience in modeling engine and the work will be to adapt existing models for simulation of hybrid vehicles.
  • Applying global optimization techniques – Genetic Algorithms (GA) and / or Differential Evolution (DE) – to solve the problem of optimal control of a hybrid engine for different optimization objectives (CO2 emissions, cost, emissions, etc.) and driving situation, considering different constraints simultaneously (hard and soft) on the system.
  • Analyze and understand the effect of different design parameters and operation on the optimal control strategy, such as:
    • The effect of optimization objective (energy, cost, CO2 emissions, etc..).
    • The effect of the constraints (soft and hard).
    • The effect of driving cycle.
    • The effect of the engine characteristics, and particularly the cost of the starting process (emissions, durability, etc.).
  • Studying the effect of simplified vehicle models and evaluating how much the quasistationary models differs from the optimum solution obtained by a MVEM. 
  • Derive implementable control laws in real time considering the effect of temperature on engine emissions and the cost of starting and stopping processes. These laws we be derived from the optimal solution obtained by global optimization techniques.
Given the nature of the project, it requires a multidisciplinary approach covering the domains related to the engine modeling, control and global optimization. The team is composed by researchers from the  Institute CMT-Motores Térmicos and Control Predictivo y Optimización Heurística (CPOH) from the  Institute of Automatic and Industrial Informatic (ai2).

KEYWORDS: Hybrid Vehicles, Global Optimization, Energy Management, Optimal Control.

In colaboration with  CMT – Motores Térmicos from Universitat Politècnica de València.