Practical Considerations for the Implementation of Dynamic Programming for HEV Powertrains

Lempert, Jeremy; Vadala, Brynn; Arshad-Aliy, Kamran; Roeleveld, Joel; Emadi, Ali

doi:10.1109/itec.2018.8450171

Cited by 24 publications

(4 citation statements)

References 8 publications

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“…Assuming overall a priori knowledge of future driving conditions for the drive cycle under analysis, the global optimal solution for the full HEV control problem with constraints on smooth driving, battery SOC and battery SOH can be found by exploiting the Bellman's principle of optimality [28]. Deterministic DP can be implemented in this framework as a well-known procedure to evaluate global optimal HEV control trajectories [29,30]. In general, the optimal HEV control solution is evaluated by DP by exhaustively sweeping all possible discretized control actions while solving an optimization problem backwardly form the final time instant to the initial one of the considered driving mission [31,32].…”

Section: Baseline Dp Formulationmentioning

confidence: 99%

Dynamic Programming Based Rapid Energy Management of Hybrid Electric Vehicles with Constraints on Smooth Driving, Battery State-of-Charge and Battery State-of-Health

Anselma

2022

Energies

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Dynamic programming (DP) is currently the reference optimal energy management approach for hybrid electric vehicles (HEVs). However, several research concerns arise regarding the effective application of DP for optimal HEV control problems which involve a significant number of control variables, state variables and optimization constraints. This paper deals with an optimal control problem for a full parallel P2 HEV with constraints on battery state-of-charge (SOC), battery lifetime in terms of state-of-health (SOH), and smooth driving in terms of the frequencies of internal combustion engine (ICE) activations and gear shifts over time. The DP formulation for the considered HEV control problem is outlined, yet its practical application is demonstrated as unfeasible due to a lack of computational power and memory in current desktop computers. To overcome this drawback, a computationally efficient version of DP is proposed which is named Slope-weighted Rapid Dynamic Programming (SRDP). Computational advantage is achieved by SRDP in considering only the most efficient HEV powertrain operating points rather than the full set of control variable values at each time instant of the drive cycle. A benchmark study simulating various drive cycles demonstrates that the introduced SRDP can achieve compliance with imposed control constraints on battery SOC, battery SOH and smooth driving. At the same time, SRDP can achieve up to 78% computational time saving compared with a baseline DP approach considering the Worldwide Harmonized Light Vehicle Test Procedure (WLTP). On the other hand, the increase in the fuel consumption estimated by SRDP is limited within 3.3% compared with the baseline DP approach if the US06 Supplemental Federal Test Procedure is considered. SRDP could thus be exploited to efficiently explore the large design space associated to HEV powertrains.

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Section: Baseline Dp Formulationmentioning

confidence: 99%

Dynamic Programming Based Rapid Energy Management of Hybrid Electric Vehicles with Constraints on Smooth Driving, Battery State-of-Charge and Battery State-of-Health

Anselma

2022

Energies

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“…The DP approach examines the driving mission backwardly from its final time step back to the first one, evaluating the cost function for each discretized control value at each discretized state value (Anselma et al (2019a)). A global optimal solution for the HEV fuel economy evaluation can be achieved in this way by operating an exhaustive search among all possible control actions at each time step of the driving mission (Lempert et al (2018)). However, due to its operating principle, DP suffers from excessive computational cost (Liu and Peng (2008)).…”

Section: Hev Rapid Controlmentioning

confidence: 99%

Multidisciplinary design optimization for hybrid electric vehicles: component sizing and multi-fidelity frontal crashworthiness

Anselma

Niutta

Mainini

et al. 2020

Struct Multidisc Optim

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“…Optimization-based energy management strategies are further divided into global optimization based and instantaneous optimization based [6]. Global optimization-based strategies, such as dynamic programming (DP) [13][14][15] and Pontryagin's minimum principle (PMP) [16][17][18], can solve the best global control sequence by traversal search under global prior information. However, the global optimization-based strategies are difficult to apply in practice projects because of the heavy computational load.…”

Section: Introductionmentioning

confidence: 99%

A Dual-Adaptive Equivalent Consumption Minimization Strategy for 4WD Plug-In Hybrid Electric Vehicles

Guo

Chu

et al. 2022

Sensors

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Energy management strategies are vitally important to give full play to energy-saving four-wheel-drive plug-in hybrid electric vehicles (4WD PHEV). This paper proposes a novel dual-adaptive equivalent consumption minimization strategy (DA-ECMS) for the complex multi-energy system in the 4WD PHEV. In this strategy, management of the multi-energy system is optimized by introducing the categories of future driving conditions to adjust the equivalent factors and improving the adaptability and economy of driving conditions. Firstly, a self-organizing neural network (SOM) and grey wolf optimizer (GWO) are adopted to classify the driving condition categories and optimize the multi-dimensional equivalent factors offline. Secondly, SOM is adopted to identify driving condition categories and the multi-dimensional equivalent factors are matched. Finally, the DA-ECMS completes the multi-energy optimization management of the front axle multi-energy sources and the electric driving system and releases the energy-saving potential of the 4WD PHEV. Simulation results show that, compared with the rule-based strategy, the economy in the DA-ECMS is improved by 13.31%.

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Practical Considerations for the Implementation of Dynamic Programming for HEV Powertrains

Cited by 24 publications

References 8 publications

Dynamic Programming Based Rapid Energy Management of Hybrid Electric Vehicles with Constraints on Smooth Driving, Battery State-of-Charge and Battery State-of-Health

Dynamic Programming Based Rapid Energy Management of Hybrid Electric Vehicles with Constraints on Smooth Driving, Battery State-of-Charge and Battery State-of-Health

Multidisciplinary design optimization for hybrid electric vehicles: component sizing and multi-fidelity frontal crashworthiness

A Dual-Adaptive Equivalent Consumption Minimization Strategy for 4WD Plug-In Hybrid Electric Vehicles

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