Reframing Automotive Fuel Efficiency
ISSN: 2640-642X, e-ISSN: 2640-6438
Published April 16, 2020 by SAE International in United States
Citation: Lovins, A., "Reframing Automotive Fuel Efficiency," SAE J. STEEP 1(1):59-84, 2020, https://doi.org/10.4271/13-01-01-0004.
Electric powertrains’ astounding recent progress often eclipses comparable energy-saving potential from aggressively reducing tractive load, especially by ambitious lightweighting. Both strategies are valid and important, but their diverse benefits—transcending simple competition for fuel savings—are partly shared, often differentiated and synergistic, and all worth capturing. Far from becoming superfluous once traction is electrified, severalfold-lower tractive load can make electrification much cheaper, easier, and faster, with major side benefits. Yet these two strategies are currently out of balance, misallocating capital, effort, and time. That imbalance is amplified by the standard method for analyzing potential automotive efficiency gains—incremental and technology-by-technology. This highly refined methodology is valid for modest changes in components, but not for major changes in whole vehicles. Fifteen market vehicles and industry designs demonstrate that incremental technology analysis dramatically understates the fuel savings available from integratively designed vehicles and overstates their marginal cost. This analytic deficiency is stranding most industry strategies and government policies severalfold short of their proven efficiency potential. Traditional analytic methods and foresight processes thus need better concepts, sources, and formats. Industry incumbents—already challenged by insurgents in design, technology, finance, business model, and culture—can ill afford the further handicap of assuming that automotive efficiency potential is severalfold smaller and costlier than integrative design can actually achieve. And, in a world at risk from oil-linked conflict, disease, and climate change, the industry that holds so much of both problem and solution must not divert its unique capabilities and precious time to suboptimal choices.