{'fraction_non_alphanumeric': 0.019682539682539683, 'fraction_numerical': 0.0019047619047619048, 'mean_word_length': 5.594142259414226, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Eco-driving Control of Electric Vehicle with Traffic Signals and Battery Dynamic Model

Nearly zero emission rate in Electric Vehicles (EVs) has made them popular and dominant in automobile industry. However, short discharging time of batteries cause major hindrance in considering them as conventional vehicles for long routes with number of traffic signals. Stop&Go scenario, which is caused due to traffic and signals on the roads, increase cohesion and energy consumption by applying brakes and reacceleration. In this paper, comparative energy analysis is applied between applying brakes at the signals and crossing them during their green time. Pontryagin’s Minimum Principle (PMP) is used as an optimal control algorithm with traffic signals as interior point constraints. Zero order battery dynamic model with detailed internal resistance and open circuit voltage characteristics is considered with constraints on State of Charge (SOC). Controlled charging and discharging behavior through constraints on battery dynamics extend battery’s life cycle. Simulation of Urban Mobility (SUMO) is used to design the route with multiple traffic signals and speed limits. Results have shown 15% improvement in energy consumption with considered approach of crossing the signals during their green duration. Furthermore, soc dependent open circuit voltage, voc and internal resistance, r0 have proven useful for the detailed analysis of the system. Achieved average motor efficiency on optimal torque and angular velocity breakpoints further strengthen the validity of results.