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IC engines have been the dominant automotive powertrain in the 20th century because of their advantages in power density, thermal efficiency, simplicity, durability and mobility. Condensing 100 years of information on automotive engine system technology evolution shows five different development stages: “bone and muscle”, “instinct”, “nerve and brain”, “intelligence”, and “system optimization”. Currently, the last step is facing the pressure of the “clean revolution” plus the “e-commerce revolution”. To meet future emission requirements and reduce CO2 emissions, the conventional engine system will be pushed to new physical limits, leading to higher cost and reduced durability. Therefore, the automobile industry should consider re-engineering or system optimization of the engines, including configuring the system architecture to be as transparent as possible to suit the fast changing environment of e-commerce.

Hydrogen Internal Combustion Engine (H2ICE) powered vehicles have been considered a low emission, low cost, practical method to help establish a hydrogen fueling infrastructure. However, the naturally aspirated H2ICE operating lean has performance issues requiring either increased displacement or induction boost to have comparable power to the modern gasoline powered IC engine. Ford Scientific Research Laboratory has continued its H2ICE system investigation, conducting dynamometer engine-boosting experiments utilizing a 2.0 L Zetec engine (with compression ratios of 14.5:1 and 12.5:1), and a 2.3L Duratec HE-4 engine (with a compression ratio of 12.2:1) with boosted manifold air pressure up to 200 kPa. Test data of brake torque and exhaust emissions are reported at various boost pressures. Results of a detailed NOx study, conducted at University of California - Riverside, with EGR and aftertreatment for a naturally aspirated 2.0L Zetec engine are also reported.

The AFR control accuracy in the cold start is crucial to lowering emissions from IC-engine vehicles. An artificial UEGO “sensor” for estimating the real-time AFR during the engine cold start has been developed on the basis of a fuel-perturbation algorithm at Ford Scientific Research Labs. The AFR values calculated by the artificial UEGO sensor have been used in the closed-loop fuel control. Considering that the engine cold start AFR is an uncertain, non-linear problem, some other techniques for optimizing the input stimulation signal and the output-filtering model are integrated together with the fuel perturbation. This artificial sensor was realized and its performance was tested on a Ford vehicle for EPA75 cold 505 test. The assessment of the artificial sensor was quite different in comparison with that of a real UEGO sensor.