Constructing Emission-Intensive Driving Cycles for an Extended-Range Electric Vehicle via Dynamic Programming Guided by Real-World Trip Dynamics and Road Terrain

Reproducing severe emission driving scenarios on a chassis dynamometer enables the systematic calibration of real driving emissions (RDE) under laboratory conditions. Accordingly, a dynamic programming (DP) method is proposed to construct emission-intensive driving cycles for an extended-range electric vehicle. The DP approach transforms the driving cycle construction problem into one of multi-stage decision optimization within a time control domain. Assembling a real driving emission model and a multi-stage decision optimization model, a DP algorithm was developed. Guided by real-world trip dynamics and road terrain, the DP algorithm optimizes instantaneous vehicle driving conditions at every time step, thereby reconstructing vehicle speed and road gradient profiles to maximize pollutant emissions within the time control domain. Analysis demonstrates that the DP algorithm favors constructing emission-intensive driving cycles using high-frequency, low-intensity acceleration and deceleration maneuvers, in addition to the high-aggression driving typically assumed to cause the severest emissions. Furthermore, the DP algorithm also effectively utilizes the impact of road terrain on emissions to construct these driving cycles. Verification confirms that the constructed emission-intensive driving cycles not only exhibit severe emission characteristics but also conform to the mandatory RDE test requirements in trip dynamics and road terrain conditions.