In order to meet the 2025 CAFÉ requirements of 54.5 MPG, automakers have been focusing on development of advanced engine technologies relying upon hybrid powertrains. The growth of these hybrid technologies is clearly illustrated today — of the 31 contenders in the 2016 Wards 10 Best Engines competition, only two are naturally aspirated inline-4s working free of hybrid drivetrains.

As compared to the gasoline engine, which has been developed over a hundred years, hybrid technologies lack a robust foundation of knowledge. The increased complexity of the hybrid engine involves the integration of mechanical, electronic and software components, making systems engineering — and the creation of a virtual environment for quick evaluation of ‘what if’ scenarios to compensate for this lack of experience — crucial to the process. There is neither enough time nor resource to physically build and test all the potential scenarios needed to ensure optimal performance of a complete hybrid powertrain system.

This is where the RFLP (Requirement, Functional, Logical, and Physical) approach to systems engineering significantly contributes to a more robust and efficient development process. As discussed in a previous blog, RFLP provides a collaborative engineering methodology that can capture, manage and track product requirements with full traceability, all from one engineering desktop window.

Here’s how this approach might play out in the development of hybrid engine technology. At the Requirements level, it’s understood that there is a need for an engine that produces a certain amount of torque – it can be any kind of engine. The requirements also state specific mass, size, and other requirements. Once the requirements are defined, system architects begin the “F” functional decomposition of the product.

At this phase, descriptions of “what” functions must be performed to satisfy the requirements are clearly defined. Users understand that they have to produce power and torque, but there are different ways to fulfill the requirement. If they choose to produce the power via a combustion engine, this then leads to a need for air intake, fuel intake, compression, ignition, power transfer and exhaust. But, the engine could still be a diesel, traditional gas, direct injection, etc.At this functional level, it will also be discovered that in producing the power and torque, heat will be created, and that heat has to be managed. This leads to fulfilling a cooling requirement. Additionally, there is the noise that the power and torque will produce; which has to be designed to meet the NVH targets.

The next step — the “L” logical piece defines “how” the functional requirement will be achieved, and there can be multiple ways to achieve these. For example, in order to produce the combustion, there is a need for a combustion system, which consists of features that allow air and fuel to enter the combustion chamber, the exhaust system to deal with waste, etc. If a gasoline direct-injection engine is the best solution to meet the requirements, this would indicate the need for a compression chamber, cylinder, air intake manifold, cylinder head, etc.

Lastly is the physical “P” level where actual parts are specified to execute the logical model.There will be a need for a valve train to let the air fuel mixture come in and exhaust go out. But, how many valves are needed? Two, four, five, six?Overhead cam?Underneath?–Pushrod? Or, perhaps a brand new technology that is being developed. Whatever it is must be defined.

These decisions should be based upon meeting the requirements in an optimal fashion. If the primary requirement is fuel economy, then the solution with the least amount of mass and greatest air flow through the combustion cycle may be the best choice.

At this point, all engineering domains and solutions are linked together in a common and dynamic engineering template enabling dynamic simulation of the complete system via a virtual prototype. So, in the case of a hybrid engine, the functions being produced – power and torque – will be accomplished through two different power sources, but shown in one single model that everyone is working from.The behavior of the product in operation is assessed while various design alternatives can be tested very early on.

Numerous ‘what-if’ scenarios can be run either from a bottom-up approach — changing the real product and tracing it back to how this affects the specifications, or from a top-down approach – changing a specification and seeing how this impacts the physical product. This becomes extremely important in a dual-powertrain system as there will almost always be a trade-off in engine development. A powerful engine may be producing a lot of noise, so it can’t go in the luxury car according to noise level requirements. To make it quieter, the power needs to be reduced.

With this approach, changing the product and/or requirements is completely traceable as to how it impacts the other systems. The requirements are directly linked to the design decision – performance, fuel economy, or cost will all directly influence the design choice. The logic that drove the decision to select that part is transparent to all users in the system.

Testing the performance of a given engine and electric motor combination to ascertain real-world performance and fuel economy is critical in delivering successful hybrid design. Understanding how the hardware components of the driveline –engine, motor; and an energy storage device interact with each other as well as with the rest of the vehicle including the torque converter, transmission, fuel storage system, HVAC system, high level vehicle controller, accessory loads, etc. requires a common engineering process that can link changes back to requirements. The only way to manage this level of complexity and interaction is through a model-based pro-active RFLP systems engineering approach.

Engines are increasingly evolving to include multiple technologies that power the vehicle – turbocharged, battery-electric, flex-fuel, turbodiesel, etc. Model-based engineering as produced by the RFLP process can speed development and control cost, helping automakers meet their targets in a more efficient manner.

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