Component Sizing and Real time Control using the A-ECMS method in a Parallel HEV

The automotive sector is constantly trying to develop new strategies to decrease the consumptions and to improve the performances. The market and the world need are converging with a paradigm shift to the renewable sources. At the present time the two options of the Electric Vehicle (EV) and the Hybrid Electric Vehicle (HEV) are two of the best perspective in which we can put our efforts. The first one, the EVs, is still limited by technical and engineering issues due to the knowledge of this time, in particular about the Energy density of the batteries. From this issues started to develop the possibility to associate an Ice Combustion Engine (ICE) to the Motor-Generator Unit (EM) with the HEVs technology. This field is huge and in continuous growth, the market in particular is leading the attention on the Parallel technology for which the motion units cooperate to develop the power for the user, it’s one of the easiest way to design an HEV but it’s still possible to reach values of Fuel Consumption that are really lower than the Traditional Vehicle, keeping also the performances able to afford every kind of situation of the real driving life and also maintaining an high driving pleasure for the journey. In this work the aim is to develop an online controller, in Real-Time for the real driving life, for and HEV with a parallel configuration P1 (one ICE and one MGU). The controller use the Adaptive Equivalent Consumption Minimization Strategy (A-ECMS) based on an Equivalent Factor (EF) between the cost of the Power developed by the ICE and the GMU, the controller can see only the request of torque of that precise instant, obtained from the speed and the acceleration of the vehicle, and the state of all the components of the HEV: battery, transmission, GMU and ICE. The difficulty is to have the possibility to reach the Charge Sustain (CS) when the car will reach the destination, which is to say keeping the same value of the State of Charge (SOC) of the battery at the time in which the vehicle started the track. This condition must be respected, not knowing what the future driving conditions would be. Once developed a controller that can reach the CS in different simulated driving cycles the second goal is to develop an algorithm that can investigate the design space looking for a combination of ICE, GMU, Battery and gear ratios for the transmission that can decrease the FC keeping the sufficient performances to deal with every kind of situation of the real driving life. The data to develop the design space are taken from the library of Amesim by Siemens, that is public and also really reliable. It has been chosen a Particle Swarm Optimization (PSO) algorithm for this aim, for his good qualities with this kind of problem, the PSO would take into account as said of both the FC and of a perfomance index in his cost function. All the study is taking in consideration as a Benchmark the values provided by the Slope-Weighted Energy-Based Rapid Control Analysis (SERCA) algorithm for the controller, that is an offline controller that could reach the optimal result for the FC with a lower computational effort than the Dynamic Programming (DP).