EFFICIENT HYBRID PROPULSION SYSTEM DEVELOPMENT AND VEHICLE INTEGRATION

This paper will incorporate product development methodology from the FED program where AVL is responsible in collaboration with World Technical Services Inc., for delivering a fully developed hybrid propulsion system integrated into the demonstrator vehicle. Specifically, the paper will discuss via case study the unique methodology employed by AVL Powertrain to develop, validate, and integrate our hybrid propulsion system into the FED vehicle. Content will include traditional and virtual powertrain development methodologies that maximize product development efficiency, ensure a robust final design, and minimize development costs. Hybrid controls development, calibration techniques and vehicle design issues will also be discussed. Proceedings of the 2011 Ground Vehicle Systems Engineering and Technology Symposium (GVSETS) Efficient Hybrid Propulsion System Development and Vehicle Integration. UNCLASSIFIED Page 2 of 10 INTRODUCTION Today’s emphasis on rapid development cycles and utilization on commercial off-the-shelf (COTS) components, to minimize total costs and time to production, has stressed the need for a high amount of upfront design and planning. The boundaries and constraints of the programs technical objectives have pushed the component decision stage further and further forward requiring a deeper knowledge of potential roadblocks and the ability to react quickly with ever-changing difficulties. A thoughtful methodology for execution of development, validation and integration of the hybrid system is critical to achieve a robust and cost effective solution. This paper is a follow-up of [1]. It will discuss AVL Powertrain Engineering, Inc. (PEI) methodologies used during the control development stages of the Fuel Efficient Ground Vehicle Demonstrator (FED) project to increase the development efficiencies and reduce program timing and costs while maintaining a robust solution. MODELING AND SIMULATION Advanced vehicle modeling and simulation is performed in AVL CRUISE [2] software for the prediction of vehicle fuel economy and performance. This also assists in appropriate cost and effective sizing of system components. The vehicle dynamics and standard powertrain components are modeled in AVL CRUISE, whereas the hybrid control algorithm and advanced powertrain components are developed utilizing model based design in MATLAB/SIMULINK and deployed as a standalone dll for use within CRUISE (See section DLL inclusion to AVL CRUISE). Some of the most important aspects of this type of modeling/simulation are to strike the right balance between modeling complexity, transparency and accuracy and the ability to utilize real measurements and parameters within the simulation model [3,4,5]. Moreover, it is also important to build a single core control model in order to minimize effort of developing and maintaining separate models for simulation and target hardware. Figure 1 shows an overview of the hybrid system layout with main powertrain components from a system viewpoint. This initial vehicle model is then used to develop, test and compare a number of power and energy management strategies. The main goal of the algorithm development is to improve fuel economy by optimizing the overall hybrid system efficiency while maintaining vehicle drivability and performance. AVL CRUISE Control Design With the vast number of COTS components that are now available for use for hybrid development vehicles, system architects and control algorithm designers need to be able to maintain flexibility in their model layout. Figure 2 gives a top level description of the simulation model. There are three propulsion sources in this vehicle: Internal Combustion Engine (ICE) (orange),an Integrated Starter Generator (ISG) (purple) and the front motor Figure 1 Hybrid System Layout Figure 2 AVL CRUISE model overview Proceedings of the 2011 Ground Vehicle Systems Engineering and Technology Symposium (GVSETS) Efficient Hybrid Propulsion System Development and Vehicle Integration. UNCLASSIFIED Page 3 of 10 (FMOT) (purple). As mentioned before, a model based approach is used for the control algorithm development. AVL CRUISE consists of longitudinal vehicle dynamics and all powertrain components. These include: ICE, engine disconnect clutch, ISG, 6-speed automatic transmission, differential, final drives at the rear axle; FMOT, 2-speed manual transmission, differential, final drives at the front axle; and battery, wheel end reduction units (WERU) and wheels connecting the two axles together. ICE and ISG constitute a parallel hybrid system whereas the inclusion of the FMOT adds Through-The-Road (TTR) hybrid functionality [6]. The main task of the energy management and control design is to utilize all three propulsion sources in the most fuel efficient manner while ensuring minimal performance characteristics. The controller model developed consists of signal conditioning and powertrain management functions including driver demand calculation, torque management, safety limit monitoring and fault tolerance, component/local and system/global efficiency calculations, power split based on energy management and real-time optimization. Three main modes of powertrain operation are 1) Engine only, 2) EV only and 3 Hybrid. There is a great emphasis of smooth transitions between these different modes under varying driving conditions. Rigorous dynamometer testing is performed to characterize and perform initial integration of main hybrid components. The data gathered from the dynamometer testing is used to further fine tune and improve vehicle simulation and control software. Samples of the types of characterization data needed for different powertrain components include; efficiencies, full load curves, thermal characteristics, fuel maps, and shift maps. These key characteristics are confirmed during the dynamometer testing phases and fed back into the base simulation to adjust control parameters and strategy. These modifications can further help steer performance and fuel economy improvements. DLL inclusion to AVL CRUISE Through Model-Based-Design (MBD), today’s control software has become a living document which provides many different functions along the software development cycle; Requirements Specification, Documentation, and Validation. One prime reason to embrace this controls approach is to achieve cross-platform deployment. By constructing the core application code utilizing a MBD approach, the container in which the control code is executed can be relocated based upon the desired usage. Figure 3 shows how the same application code can be recompiled using a hardware abstraction layer (HAL) to be used either for target application or inclusion into a software-in-the-loop (SiL) simulation environment for verification and help induce a quicker development cycle. Once the application code has been translated into the appropriate format, it can be utilized by different functional developers. For System Level Development, the code can exist as a component inside AVL CRUISE, see Figure 4. For Controls Level Development, the vehicle model can be included as a component inside of the application development environment, see Figure 5. Each functional developer can concentrate on their own unique area of expertise, while both utilizing the others latest development release. Figure 3 MBD Application Code Abstraction Figure 4 AVL CRUISE System Level Development Proceedings of the 2011 Ground Vehicle Systems Engineering and Technology Symposium (GVSETS) Efficient Hybrid Propulsion System Development and Vehicle Integration. UNCLASSIFIED Page 4 of 10 Component Re-evaluation As described earlier, one of the main objectives of performing simulations is to help in sizing of available COTS components. Individual component selection criteria is based on efficiency, performance and drivability requirements with respect to overall system cost. After architectural concept selection and initial procurement, components once eliminated needed to be re-evaluated when commercial issues arose. One such issue was the transmission selection. Initially an Automatic Manual Transmission (AMT) was selected for two separate reasons; 1) to reduce driveline efficiencies and 2) to allow pure EV drive mode, since the input shaft could come to a standstill. During procurement, issues arose with the vendor which forced us to re-evaluate the cost benefit tradeoff between the AMT and a standard Automatic Transmission. Rapid modeling changes and initial control development allowed evaluation of alternative solutions and vendors. To overcome the EV drive issue utilizing a torque converter, the ISG must maintain an idle speed control loop to supply the required hydraulic pressure. (See section Calibration Challenges for issues arising from this) Plant Model Reduction The energy management algorithm calculates component energy availability, driver demanded torque and manages the distribution of power between propulsion components. This includes a real-time optimization function for the power split between the three propulsion sources, namely ICE, ISG and FMOT. This task is found to be potentially computationally intensive and demanding in comparison to other hybrid control functionality. This efficiency based power split uses pre-determined and stored efficiency maps for the ICE, ISG, FMOT, front and rear transmissions and final drives. In order to have the modeled code execute within the embedded target selected, several simplifications are needed including reduction of efficiency map lookup table sizes and adjustment of processor foreground task timing. For the optimization task, an objective function is constructed that reflects the overall power loss in the main powertrain components. This constitutes a minimization problem that requires evaluation over several iterations. In order to minimize the computational effort, a careful compromise is required between the number of iterations and the mini